Diagnosis and treatment of mesothelioma

ABSTRACT

This disclosure provides methods for surveillance, early detection and diagnosis, subtype classification, prediction of recurrence, prognosis and therapy of malignant mesothelioma based on profiles of indicator mutations in disclosed genes.

CROSS REFERENCE TO RELATED APPLICATIONS

This application claims benefit under 35 U.S.C. §119(e) of U.S. Provisional Application No. 61/550,747 filed on Oct. 24, 2011 and U.S. Provisional Application No. 61/551,058 filed on Oct. 25, 2011, the contents of which are incorporated herein by reference in their entirety.

FIELD

The disclosure herein relates to surveillance, diagnosis, subtype classification, and therapy of malignant mesothelioma.

BACKGROUND

Malignant mesothelioma (MM) is a highly aggressive neoplasm, arising from the mesothelial surfaces of the pleural and peritoneal cavities, the pericardium, or the tunica vaginalis, and is commonly described as associated with a history of asbestos exposure, although other causes such as viral infection has been implicated. With median survival durations of 8-18 months from onset of symptoms, the prognosis is poor.

One of the reasons for the poor prognosis is the difficulty in early diagnosis. Early detection and diagnosis affords the patient greater therapy options and the opportunity to curb the spread of cancer. Mesothelioma is a disease that is characterized by a long latency period. The latency period is the amount of time that elapses from the first point of asbestos exposure or exposure to other initiators such as viral infections to the point where symptoms begin to appear so that a diagnosis can be made. In some mesothelioma cases the latency period is reported to be 10 years but the average latency for the majority of cases is between 35 and 40 years. As a result, the cancer often progresses to later stages before a diagnosis is made. When diagnosed in the later stages, mesothelioma treatment options become more limited and are less effective. Also, the early symptoms of mesothelioma are generally non-specific and are similar to a variety of common respiratory ailments, and can lead to a delay in diagnosis. Current differential diagnosis of mesothelioma comprises elimination of common respiratory ailments, followed by confirmatory diagnosis by imaging techniques such as chest x-ray, CT scan or MRI, and by biopsy and cytological methods such as evidence of cancerous cells in pleural effusion or pleura.

Another reason for the poor prognosis is the limited therapy for the disease. Current therapy comprises mainly surgical and chemotherapy, but chemotherapy remain toxic and selection of appropriate patients for these therapies is difficult. Surgical therapies are pleurectomy/decortication (P/D) and extrapleural pneumonectomy but they are applicable only if there is limited metastasis. When there is substantial metastasis such that surgery is not a curative option, palliative surgery can be performed to remove the cancerous tissue or help with the drainage of excess fluid to provide relief from symptoms and alleviate pain. While palliative surgery does not offer a cure, such treatment has improved quality of life and prolonged survival. While there are a number of chemotherapy drugs, they are less effective in later diagnosed mesotheliomas that have metastasized.

SUMMARY

Embodiments of this disclosure are based on the discovery of specific genetic mutations that are associated with malignant pleural mesothelioma (MPM) (see Tables 1 and 2). These genetic mutations are biomarkers of MPM. Thus, these biomarkers are useful for early diagnosis of malignant mesothelioma (MM), particularly MPM, for generating a new classification of MM subtypes, for subtyping of new MM patients, for selecting and monitoring optimal treatment regimens, for monitoring MM patient treatment prognosis and outcome, and for treatment of MM.

Accordingly, in one embodiment, it is the objective of this disclosure to provide a method of surveillance and early diagnosis of mesothelioma.

In one embodiment, it is the objective of this disclosure to provide a method of generating a new classification of MM subtypes.

In one embodiment, it is the objective of this disclosure to provide a method of subtyping of new MM patients, and also for selecting and monitoring optimal treatment regimens.

In another embodiment, it is the objective of this disclosure to provide a method of prognosis evaluation of MM during treatment.

In another embodiment, it is the objective of this disclosure to provide therapeutic targets for the treatment of MM in addition to the existing repertoire of cancer therapies currently available.

In one embodiment, the disclosure herein provides a method for surveillance for MM or early detection or early diagnosis of MM in a subject in need thereof comprising: (a) detecting the presence of at least one genetic mutation listed in Tables 1 and 2, and FIG. 1 in a biological sample obtained from the subject; and (b) subjecting the subject to at least one addition diagnostic test selected from the group consisting of chest X-ray, MRI, CT scan, PET scan, thoracentesis, mediastinoscopy, echocardiogram and thoracoscopy when at least one mutation is detected. In one embodiment, the MM is malignant pleural mesothelioma (MPM). In one embodiment, the mutation is not one that is listed on Table 2.

In one embodiment, the disclosure herein provides a method for surveillance for MM or early diagnosis or early detection in a subject in need thereof comprising: (a) detecting the presence of at least one genetic mutation in a tumor necrosis factor receptor superfamily member 1A (TNFRSF1A) gene in a biological sample obtained from the subject; and (b) subjecting the subject to at least one addition diagnostic test selected from the group consisting of chest X-ray, MRI, CT scan, PET scan, thoracentesis, mediastinoscopy, echocardiogram and thoracoscopy when at least one mutation is detected. In one embodiment, the at least one genetic mutation in the TNFRSF1A gene is selected from a A→G at 113 base pair (bp) from the ATG start codon of the mRNA shown in FIG. 1; a A→G at 268 bp from ATG, and a C→T at 712 bp from ATG. In some embodiments, the presence of more than one genetic mutation is surveyed, for example, the presence of two or all three mutations of TNFRSF1A are surveyed.

In some embodiments, more than one genetic mutation is surveyed, for example, two, three, four, five, six, seven, eight, nine, or ten genetic mutations disclosed in Tables 1 and 2 are surveyed.

In one embodiment, the surveillance method is performed once a year, e.g., during an annual physical examination. In other embodiments, the surveillance method is performed monthly, once every two months, once every three months, once every two months, once every five months, or once every six months.

In one embodiment, the surveillance method is used for surveillance of recurrence of the disease. Recurrence in deemed to occur when there is an increase in the number of mutations compared to the number of mutations obtained from an earlier surveillance when the subject is in remission. For example, there is zero, one or only two mutations at remission.

In one embodiment, the subject has not been differentially diagnosed with MM, for example, MPM.

In one embodiment, the subject is male. In another embodiment, the subject is female. In one embodiment, the subject is in need of such surveillance or early detection, e.g., the subject is at risk of developing MM. In one embodiment, the method comprises selecting a subject in need of such surveillance or early detection or early diagnosis.

In one embodiment, the subject is between the ages of 35-95.

In one embodiment, the subject is 50 years and older.

In one embodiment, the subject has prior exposure to asbestos.

In some embodiments, the subject lives or has lived with a person who works with asbestos or had prior exposure to asbestos. In other embodiments, the subject does not live or has not lived with a person who works with asbestos or had prior exposure to asbestos.

In one embodiment, the subject has no known prior exposure to asbestos.

In one embodiment, the subject is asymptomatic for a common respiratory ailment.

In another embodiment, the subject has at least one symptom selected from the group consisting of anemia, a blood clotting disorder, bowel obstruction, chest pain, persistent dry or raspy cough, coughing up blood (hemoptysis), shortness of breath (dyspnea), pain in the lower back or rib area, painful breathing, development of lumps under the skin on the chest, difficulty with swallowing (dysphagia), night sweats or fever, nausea, unexplained weight loss, fatigue, abdomen, pericardium, peritoneal and/or pleural effusion.

In one embodiment, the detection of genetic mutations disclosed in Tables 1 and 2, and disclosed TNFRSF1A mutations comprises providing the biological sample obtained from the subject; extracting the nucleic acid (e.g., DNA or RNA) from the biological sample; and analyzing for the presence of at least one mutation. In another embodiment, extraction of the DNA from the biological sample is not required.

In some embodiments, the biological sample includes but not limited to blood samples, plasma, serum, urine, sweat, peritoneal fluid sample, and any tissue sample of the body, including tumor tissue samples.

In one embodiment, the method further comprises detecting for the presences of all the mutations disclosed in Tables 1 and 2, disclosed TNFRSF1A mutations to generate a profile of gene mutations for the subject. This profile of gene mutations is then used to categorize the subject into the subtypes of MPM generated herein.

In one embodiment when at least one mutation is detected in the biological sample from the subject, the method further comprising assigning a subtype of MPM to the subject based the profile of gene mutations obtained from the subject.

In one embodiment when at least one mutation is detected in the biological sample from the subject, the method further comprises inputting the profile of gene mutations into a computer system equipped with a computer software for analyzing the profile of gene mutations and assigning a subtype of MM to the inputted profile of gene mutations.

In one embodiment, the disclosure herein provides a method of classifying MM into subtypes based on profiles of genetic mutations in a population of subjects having MM comprising: (a) providing a genetic mutation profile database comprising a library of profile of genetic mutations of the genes of Tables 1 and 2 at the specific location indicated in Tables 1 and 2, and disclosed TNFRSF1A mutations, wherein the profiles are derived from a population of subjects having MM, and wherein the profiles are from biological samples obtained from the subjects prior to any treatment; (b) applying the genetic mutation database to a clustering algorithm which analyzes and identifies at least two separate and distinct clusters within the database, wherein each cluster comprising a unique collection of genetic mutations disclosed in Tables 1 and 2, and disclosed TNFRSF1A mutations; (c) sorting the population of subjects having MM into the at least two separate and distinct clusters identified by the clustering algorithm; (d) monitoring the treatment regimen and prognosis of the subjects separated into the clusters of step (c); correlating the treatment regimen and prognosis of the subjects with the subject's designated cluster; (e) determining which treatment regimen for each cluster results in at least 2 fold increase in survival over the median survival time; and (f) associating the treatment regimen of step (g) with the respective cluster to form a subtype. In one embodiment, the subjects in the population have MPM. In one embodiment, the mutation is not one that is listed on Table 2.

In one embodiment, the profile of genetic mutation is obtained by providing a biological sample from each subject of the population; extracting the nucleic acid (e.g., DNA or RNA) from the biological sample; and analyzing for the presence of all the genetic mutations disclosed in Tables 1 and 2, and disclosed TNFRSF1A mutations. In another embodiment, extraction of the nucleic acid from the biological sample is not required.

In one embodiment, the step (b) and step (c) are performed using a computer system equipped with a clustering algorithm for analyzing the profiles of gene mutations and assigning a subtype of MPM to the profile of gene mutations. For example, the clustering algorithm is a k-means algorithm.

In one embodiment, the correlating is performed by executing a software classification algorithm. For example, Naive-Bayes classification algorithm.

In one embodiment, the disclosure herein provides a method of subtyping MM in a subject comprising: (a) detecting for the presences of all the mutations disclosed in Tables 1 and 2, and disclosed TNFRSF1A mutations to generate a profile of gene mutations; (b) comparing the profile of gene mutations with a collection of genetic mutations associated with each subtypes identified in the method described herein; and (c) assigning a subtype of MM when the profile of gene mutations of the subject matches the collection by a 70 percentile. In one embodiment, the subject has MPM.

In one embodiment, the profile of genetic mutation is produced by providing a biological sample from a subject; extracting the nucleic acid (e.g., DNA or RNA) from the biological sample; and analyzing for the presence of all the genetic mutations disclosed in Tables 1 and 2, and disclosed TNFRSF1A mutations. In one embodiment, extraction of the nucleic acid is not required.

In one embodiment, the comparing and assigning steps are performed using a computer system equipped with a clustering algorithm for analyzing the inputted profiles of gene mutations and assigning a subtype of MM to the profile of gene mutations.

In one embodiment, the disclosure herein provides a method for monitoring the progression or regression of a subject having malignant mesothelioma (MM), the method comprising: (a) monitoring the presence or absence of at least one genetic mutation listed in Tables 1 and 2, and disclosed TNFRSF1A mutations or listed in a collection of gene mutations characteristic of a subtype of MM in a biological sample from the subject prior to a treatment or at a first time during the course of a treatment; (b) monitoring the presence or absence of the at least one genetic mutation listed in Tables 1 and 2, and disclosed TNFRSF1A mutations or listed in a collection of gene mutations characteristic of a subtype of MPM in another biological sample from the subject at a second time during the course of a treatment, wherein the first and second time are in chronological order, and wherein the same genetic mutation(s) is monitored at in step (a) and step (b); and comparing the first measurement and the second measurement, wherein the comparative measurements determine the course of MM in the subject. In one embodiment, the subject has MPM. In one embodiment, the mutation is not one that is listed on Table 2. In some embodiments, new mutations that were not observed in step (a) may be observed in step (b).

In one embodiment, where there is no disappearance of the at least one genetic mutation during the course of treatment when the at least one genetic mutation is present prior to start of treatment or at the first time indicating progression of MM. The observation that there is no disappearance of the at least one genetic mutation during the course of treatment indicates that the treatment is not effective and terminating the treatment is recommended.

In one embodiment, where there is appearance of the at least one genetic mutation during the course of treatment when the at least one genetic mutation is absent prior to start of treatment or at the first time indicating progression of MM. The observation that there is additional genetic mutation surfacing during the course of treatment indicates that the treatment is not effective and terminating the treatment is recommended.

In one embodiment, where there is disappearance of the at least one genetic mutation during the course of treatment, when the at least one genetic mutation is present prior to start of treatment or at the first time indicating regression of MM. The observation that there is disappearance of the at least one genetic mutation during the course of treatment indicates that treatment is effective and continuing the treatment is recommended.

In one embodiment, the method further comprises commencing another treatment when the current treatment is terminated.

In one embodiment, the collection of gene mutations characteristic of a subtype of MM is determined by the method of classifying MM subtypes as described herein.

In one embodiment, the subject is identified as having a subtype of MM by the method of subtyping MM as described herein.

In one embodiment, the disclosure herein provides a method for selecting and monitoring optimal treatment regimen for a subject comprising: (a) categorizing the MM to a subtype according to the method of subtyping MM as described herein; and administering an effective treatment regime to the subject based on the subtype.

In one embodiment, the disclosure herein provides a method for treating MM in a subject comprising: (a) categorizing the MM to a subtype according to the method of subtyping MM as described herein; and administering an effective treatment regime to the subject based on the subtype.

In one embodiment, the disclosure herein provides a method for treating MM in a subject comprising administering to a subject in need thereof a therapeutically effective amount of an agent that increases the expression of a tumor necrosis factor receptor superfamily member 1A (TNFRSF1A) gene.

In one embodiment, the disclosure herein provides a method for treating MM in a subject comprising administering to a subject in need thereof a composition comprising an agent that increases the expression of a tumor necrosis factor receptor superfamily member 1A (TNFRSF1A) gene.

In one embodiment, the disclosure herein provides a composition comprising an agent that increases the expression of a tumor necrosis factor receptor superfamily member 1A (TNFRSF1A) gene for use in the treatment of MM.

In one embodiment, the disclosure herein provides a use of an agent that increases the expression of a tumor necrosis factor receptor superfamily member 1A (TNFRSF1A) gene for the treatment of MM.

In one embodiment of any methods described herein, the MM is MPM.

In some embodiment, the agent is thalidomide or lenalidomide (levlimid).

In one embodiment, the agent is a nucleic acid sequence comprising the human sequence TNFRSF1A mRNA sequence NM_(—)001065.2.

In one embodiment, the agent is a nucleic acid sequence comprising SEQ. ID. NO:1.

In one embodiment, the agent is a vector or DNA construct comprising a nucleic acid sequence of TNFRSF1A mRNA sequence NM_(—)001065.2 or SEQ. ID. NO:1.

In one embodiment of any treatment method described herein, the method further comprises administering an additional cancer therapy, wherein the at least one additional cancer therapy is selected from the group consisting of radiation therapy, chemotherapy, immunotherapy and gene therapy.

In one embodiment of any treatment method described herein, the composition is administered in conjunction with at least one additional cancer therapy to achieve a combination cancer therapy.

In other embodiments of any treatment method described herein, the at least one additional cancer therapy is a mesothelioma cancer therapy.

In other embodiments of any treatment method described herein, the mesothelioma cancer therapy includes but is not limited to carboplatin, cisplatin, cyclophosphamide, doxorubicin, gemcitabine, navelbine, onconase, paclitaxel, pemetrexed, MORAb-009, SS1(dsFv)-PE38, and bevacizumab.

In one embodiment, of any of the composition described herein, the composition is administered in conjunction with at least one additional cancer therapy to achieve a combination cancer therapy.

In one embodiment of any composition described herein, wherein the at least one additional cancer therapy is selected from the group consisting of radiation therapy, chemotherapy, immunotherapy and gene therapy

In one embodiment, the disclosure herein provides a microarray chip for rapid analysis of the presence or absence of genetic mutations disclosed in Table 1 and 2, and disclosed TNFRSF1A mutations, comprising a library of nucleic acid probes covering at least five genetic mutations disclosed in Tables 1 and 2 and FIG. 1, wherein each probe comprises single strand nucleic acid sequence that is at least 15 nucleotides long and is complementary to the at least 5 base pair 5′ and at least 3′ of the position of mutation disclosed. In one embodiment, the single strand nucleic acid sequence for each genetic mutation is present in triplicates. In one embodiment, the chip comprises probes that there single strand nucleic acid sequence of normal, non-mutated genes.

In one embodiment, the disclosure herein provides a kit for rapid analysis of the presence or absence of genetic mutations disclosed in Table 1 and 2, and disclosed TNFRSF1A mutations, the kit comprising a microarray chip described herein, PCR primers and reagents for isolating nucleic acid from a biological sample, and amplifying the gene regions encompassing the location of mutations disclosed in Table 1 and 2, and disclosed TNFRSF1A mutations. In another embodiment, the nucleic acid is not extracted or isolated from a biological sample.

In one embodiment, provided herein is a system comprising: a measuring module measuring a profile of genetic mutations comprising a detectable signal from an assay indicating the presence of at least one genetic mutation from a biological sample obtained from a subject; a storage module configured to store data output from the measuring module; a comparison module adapted to compare the data stored on the storage module with reference and/or control data, and to provide a retrieved content, and an output module for displaying the retrieved content for the user, wherein the retrieved content the presence of detectable at least one genetic mutation indicates that the subject has MM or has a relapse of MM.

In one embodiment, provided herein is a system to facilitate the prognosis evaluation of MM in a subject, comprising: a determination (measuring) module configured to receive and output the presence of at least one genetic mutation from a biological sample obtained from a subject; a storage module configured to store output information from the determination module; a comparison module adapted to compare the data stored on the storage module with reference and/or control data, and to provide a comparison content, and an output module for displaying the comparison content for the user. If there is at least one detected genetic mutation disclosed herein, then the subject likely has MM if the subject have not been previously diagnosed with MM or the subject has a relapse if the subject has been in remission and has minimal or no detectable mutations at start of remission. If there is an increase in the number of mutations, then the MM in the subject is progressing, and the current treatment is not effective. If there is a decrease in the number of mutations, then the MM in the subject is regressing, and the current treatment is effective.

In one embodiment, provided herein is a computer readable storage medium comprising: a storing data module containing data from a biological sample obtained from a subject that a profile of genetic mutations comprising a detectable signal from an assay indicating the presence of at least one genetic mutation; a comparison module that compares the data stored on the storing data module with a reference data and/or control data, and to provide a comparison content, and an output module displaying the comparison content for the user. If there is at least one detected genetic mutation disclosed herein, then the subject likely has MM if the subject have not been previously diagnosed with MM or the subject has a relapse if the subject has been in remission and has minimal or no detectable mutations at start of remission. If there is an increase in the number of mutations, then the MM in the subject is progressing, and the current treatment is not effective. If there is a decrease in the number of mutations, then the MM in the subject is regressing, and the current treatment is effective.

In one embodiment, the reference and/or control data is the genetic mutation profile of the same subject at an earlier time point, e.g., prior to start of treatment. In one embodiment, the reference and/or control data is the entire collection of mutations disclosed in Tables 1 and 2 and the human TNFRSF1A gene. In another embodiment, the reference and/or control data is the collection of mutations characteristic for the subtypes of MM according to the method described herein.

DEFINITIONS

As used herein, the term “comprising” or “comprises” is used in reference to methods, and respective component(s) thereof, that are essential to the claims, yet open to the inclusion of unspecified elements, whether essential or not. The use of “comprising” indicates inclusion rather than limitation.

The term “consisting of” refers to methods, and respective components thereof as described herein, which are exclusive of any element not recited in that description of the embodiment.

The term “reduction” is all used herein generally to mean a decrease by a statistically significant amount relative to a reference, e.g., initial number of genetic mutations in a profile. However, for avoidance of doubt, “reduce,” “reduction”, or “decrease” typically means a decrease by at least 10% as compared to the absence of a given treatment and can include, for example, a decrease by at least about 20%, at least about 25%, at least about 30%, at least about 35%, at least about 40%, at least about 45%, at least about 50%, at least about 55%, at least about 60%, at least about 65%, at least about 70%, at least about 75%, at least about 80%, at least about 85%, at least about 90%, at least about 95%, at least about 98%, at least about 99%, up to and including, for example, the complete absence of the given entity or parameter as compared to the absence of a given treatment, or any decrease between 10-99% as compared to the absence of a given treatment. In one embodiment, reduction can be by just a number, e.g., reduction by one or two mutations detected.

The terms “increased” or “increase” are all used herein to generally mean an increase by a statically significant amount; for the avoidance of any doubt, the terms “increased”, or “increase” means an increase of at least 10% as compared to a reference level, e.g., initial number of genetic mutations in a profile or the basal level of expression of TNFRSF1A. For example an increase of at least about 20%, or at least about 30%, or at least about 40%, or at least about 50%, or at least about 60%, or at least about 70%, or at least about 80%, or at least about 90% or up to and including a 100% increase or any increase between 10-100% as compared to a reference level, or at least about a 2-fold, or at least about a 3-fold, or at least about a 4-fold, or at least about a 5-fold or at least about a 10-fold increase, or any increase between 2-fold and 10-fold or greater as compared to a reference level. In one embodiment, increase can be by just a number, e.g., increase by one or two mutations detected.

As used herein, the terms “treat,” “treatment,” and the like, as used in the context of the therapeutic methods described herein, refer to a decrease in severity, indicators, symptoms, and/or markers of mesothelioma as described herein. In the context of the present technology insofar as it relates to any of the conditions recited herein, the terms “treat,” “treatment,” and the like mean to relieve, alleviate, ameliorate, inhibit, slow down, reverse, or stop the progression, aggravation, deterioration, anticipated progression or severity of at least one symptom or complication associated with mesothelioma. In one embodiment, a symptom of mesothelioma is alleviated by at least 10%, at least 20%, at least 30%, at least 40%, or at least 50% or more than 50%.

The term “amelioration” as used herein, refers to a lessening of severity of at least one indicator of a condition or disease. In certain embodiments, amelioration includes a delay or slowing in the progression of one or more indicators of a condition or disease. The severity of indicators may be determined by subjective or objective measures which are known to those skilled in the art.

The term “biological sample” as used herein means a sample of biological tissue or fluid that comprises nucleic acids. Such samples include, but are not limited to, tissue or fluid isolated from subjects. Biological samples may also include sections of tissues such as biopsy and autopsy samples, formaldehyde fixed-paraffin embedded (FFPE) samples, frozen sections taken for histological purposes, blood, plasma, serum, sputum, stool, tears, mucus, hair, and skin. Biological samples also include explants and primary and/or transformed cell cultures derived from animal or patient tissues.

Biological samples may also be blood, a blood fraction, urine, effusions, ascitic fluid, saliva, cerebrospinal fluid, cervical secretions, vaginal secretions, endometrial secretions, gastrointestinal secretions, bronchial secretions, sputum, cell line, tissue sample, cellular content of fine needle aspiration (FNA) or secretions from the breast. A biological sample may be provided by removing a sample of cells from an animal, but can also be accomplished by using previously isolated cells (e.g., isolated by another person, at another time, and/or for another purpose), or by performing the methods described herein in vivo. Archival tissues, such as those having treatment or outcome history, may also be used.

As used herein, “mesothelioma” refers to a cancer affecting the membrane linings of the lungs and abdomen. Mesothelioma is an aggressive form of cancer, and includes malignant mesothelioma. The term “mesothelioma” as used herein includes; Pleural mesothelioma (MPM) (affecting the lung's protective lining in the chest cavity, which represents about three quarters of all mesothelioma incidence), Peritoneal mesothelioma (which affects the abdominal cavity and pericardial mesothelioma, which affects the cardiac cavity), and Testicular mesothelioma (which is typically extremely rare and typically presents with metastases of the peritoneal variety). Encompassed in the term mesothelioma are mesotheliomas of the three recognized mesothelioma cell-types; epithelial cell-type mesothelioma (which comprises between 50 and 70% of all mesotheliomas), sarcomatoid mesothelioma and biphasic mesothelioma. Symptoms of mesothelioma include, but are not limited to In one embodiment, the subject has exhibited at least one symptom selected from the group anemia, blood clotting disorder, bowel obstruction, chest pain, persistent dry or raspy cough, coughing up blood (hemoptysis), shortness of breath (dyspnea), pain in the lower back or rib area, painful breathing, development of lumps under the skin on the chest, difficulty with swallowing (dysphagia), night sweats or fever, nausea, unexplained weight loss, fatigue, abdomen, pericardium, peritoneal and/or pleural effusion.

As used herein, the term “classification” or “classifying” refers to a procedure and/or algorithm in which individual items are placed into groups or classes based on quantitative information on one or more characteristics inherent in the items (referred to as traits, variables, characters, features, etc) and based on a statistical model and/or a training set of previously labeled items. According to one embodiment, classification means determination of the type of cancer. In one embodiment, classification determines a type of classification of poor or good prognosis or improved survival time or decreased survival time after diagnosis with mesothelioma.

The term “detection” as used herein means detecting the presence of a component in a sample. In one embodiment, detection also means detecting the absence of a component. In one embodiment, detection also means measuring the level of a component, either quantitatively or qualitatively. In one embodiment, detection also means identifying or diagnosing cancer in a subject. In another embodiment, “early detection” means identifying or diagnosing cancer in a subject at an early stage of the disease, especially before it causes symptoms.

The term “gene” as used herein may be a natural (e.g., genomic) or synthetic gene comprising transcriptional and/or translational regulatory sequences and/or a coding region and/or non-translated sequences (e.g., introns, 5′- and 3′-untranslated sequences). The coding region of a gene may be a nucleotide sequence coding for an amino acid sequence. A gene may also be an mRNA or cDNA corresponding to the coding regions (e.g., exons and miRNA) optionally comprising 5′- or 3′-untranslated sequences linked thereto. A gene may also be an amplified nucleic acid molecule produced in vitro comprising all or a part of the coding region and/or 5′- or 3′-untranslated or regulatory sequences linked thereto.

As used herein, “cancer” refers to any of various malignant neoplasms characterized by the proliferation of anaplastic cells that tend to invade surrounding tissue and metastasize to new body sites and also refers to the pathological condition characterized by such malignant neoplastic growths.

A “cancer” or “tumor,” as used herein, refers to an uncontrolled growth of cells which interferes with the normal functioning of the bodily organs and systems. A subject that has a cancer or a tumor is a subject having objectively measurable cancer cells present in the subject's body. Included in this definition are benign and malignant cancers, as well as dormant tumors or micrometastatses. Cancers which migrate from their original location and seed vital organs can eventually lead to the death of the subject through the functional deterioration of the affected organs.

The term “metastasis” as used herein means the process by which cancer spreads from the place at which it first arose as a primary tumor to other locations in the body. The metastatic progression of a primary tumor reflects multiple stages, including dissociation from neighboring primary tumor cells, survival in the circulation, and growth in a secondary location.

The term “survival time”, as used herein means the time period for which a subject survives after diagnosis of or treatment for a disease. In certain embodiments, the disease is mesothelioma, and in some embodiments, the disease is malignant mesothelioma (MM), and in some embodiments the disease is malignant plural mesothelioma (MPM).

The term “therapy” as used herein means a disease treatment method. In certain embodiments, therapy includes, but is not limited to chemotherapy, surgical resection, transplant, radiation therapy, “gene therapy”, immunotherapy, and/or chemoembolization. The term “therapeutic agent” means a pharmaceutical agent used for the cure, amelioration or prevention of a disease. “Recommended therapy” means a treatment recommended by a medical professional for the treatment, amelioration, or prevention of a disease.

The term “therapeutically effective amount” or “therapeutically efficient”, used herein as to a dosage of an agent that increases the expression of a TNFRSF1A, refers to dosage that provides the specific pharmacological response for which the agent is administered in a significant number of subjects in need of such treatment. The “therapeutically effective amount” may vary according to, for example, the physical condition of the patient, the age of the patient and the severity of the disease.

As used herein, the term “effective amount” is meant an amount of an agent that increases the expression of a TNFRSF1A as disclosed herein effective to yield a desired effect. The term “effective amount” as used herein refers to that amount of composition necessary to achieve the indicated effect. The specific “effective amount” will, obviously, vary with such factors as the particular condition being treated, the physical condition of the subject, the type of subject being treated, the duration of the treatment, the route of administration, the type of estrogen or estrogen mimetic being used, the nature of concurrent therapy (if any), and the specific formulations employed, the structure of each of these components or their derivatives.

The term “agent” refers to any entity which is normally not present or not present at the levels being administered to a cell, tissue or subject. Agent can be selected from a group comprising: chemicals; small molecules; nucleic acid sequences; nucleic acid analogues; proteins; peptides. A nucleic acid sequence can be RNA or DNA, and can be single or double stranded, and can be selected from a group comprising: nucleic acid encoding a protein of interest; or oligonucleotides.

The term “isolating” refers to removing materials, such as a nucleic acid or a protein, from components which normally accompany or interact with the material as found in its naturally occurring environment.

The term “vector”, as used herein, refers to a nucleic acid construct designed for delivery to a host cell or transfer between different host cells. As used herein, a vector can be viral or non-viral.

As used herein, the term “expression vector” refers to a vector that has the ability to incorporate and express heterologous nucleic acid fragments in a cell. An expression vector may comprise additional elements, for example, the expression vector may have two replication systems, thus allowing it to be maintained in two organisms, for example in human cells for expression and in a prokaryotic host for cloning and amplification.

As used herein, the term “viral vector” is used according to its art-recognized meaning. It refers to a nucleic acid vector construct that includes at least one element of viral origin and may be packaged into a viral vector particle. The vector may be utilized for the purpose of transferring DNA, RNA or other nucleic acids into cells either in vitro or in vivo. Numerous forms of viral vectors are known in the art.

As used herein, the term “recurrence” of malignant mesothelioma (MM) refers to the re-manifestation/re-development of known symptoms associated with the cancer after previous successful treatment. For example, a “recurrence” of MM refers to the enlargement of an existing tumor whose growth had stopped or reduced during therapy, or the emergence of a tumor at the original (primary) site of tumor discovery after the original tumor had been excised. The recurrence of a tumor can also mean new tumor growth(s) of the same tumor type as the original tumor at a site different from the original site of tumor discovery. This can be an indication that the original primary tumor has spread to other locations, or the primary tumor has emerged as an anti-angiogenic resistant form. In one embodiment, “recurrence” of MM refers to increase number of genetic mutations in the subject's profile of genetic mutations after a period of disease remission and symptom free. In one embodiment, the increase number of genetic mutations is having at least 30% number of genetic mutations the subject originally had before remission. In one embodiment, the increase number of genetic mutations is having at least 30% number of genetic mutations identified to be characteristic of the subject's subtype of MM. In another embodiment, the increase in number of genetic mutations is at least 2 fold or more of the number of genetic mutations the subject had during remission. For example, the subject had only one mutation during remission. If the subject now has three mutations during surveillance testing, then the subject is deemed to have recurrence or relapse of MM.

In one embodiment, the term “recurrence” and “relapse” of MM are used interchangeably.

As used herein, the term “prognosis” encompasses predictions and likelihood analysis of disease progression, particularly tumor recurrence, metastatic spread, and disease relapses. The prognosis method described herein is intended for clinical use in making decision concerning treatment modalities, including therapeutic interventions, diagnostic criteria such as disease staging, and disease monitoring and surveillance for metastasis or recurrence of neoplastic disease.

As used herein, the term “remission” with respect to malignant mesothelioma refers to the state of absence of disease activity in patients with malignant mesothelioma, with the possibility of return of disease activity. In one embodiment, “remission” refers to the situation where a patient has less than 5% of the genetic mutations identified to be characteristic of the subject's subtype of MM. In one embodiment, “remission” refers to the situation where a patient has no detectable genetic mutations disclosed in Tables 1 and 1, and the TNFRSF1A gene. In one embodiment, remission means having zero, one or only two mutations detected.

As used herein, the term “differentially diagnosed” with respect to malignant mesothelioma refers to the final diagnosis of malignant mesothelioma after all other respiratory ailments or ailments that can present similar symptoms have been systematically ruled out.

As used herein, “a profile of genetic mutations” in the context of a subject refers to a compilation or collection of genetic mutations unique to that subject.

As used herein, “subtype” in the context of malignant mesothelioma (MM) refers to a group of MM that is characteristically associated with a particular compilation or collection of genetic mutations.

As used herein, “subtyping” refers to assigning or sorting malignant mesothelioma (MM) of a subject to a particular subtype based on the profile of genetic mutations of the subject.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 shows the three point mutations identified in the human TNFRSF1A coding sequencing (SEQ. ID. NO: 2) obtained from a patient with malignant pleural mesothelioma (MPM). The point mutations are indicated in upper case nucleotide bases, A, G, C, or T.

FIG. 2 is a block diagram showing an exemplary system for MM diagnosis, surveillance, and subtyping.

FIG. 3 is an exemplary set of instructions on a computer readable storage medium for use with the systems described herein.

TABLES

Table 1. Genetic mutations in MPM patients. Locations are indicated by the nucleotide position in the chromosome of the affected gene.

Table 2. Cancer-associated genetic lesions in MPM patients.

DETAILED DESCRIPTION

Unless otherwise explained, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs. Definitions of common terms in molecular biology may be found in Benjamin Lewin, Genes IX, published by Jones & Bartlett Publishing, 2007 (ISBN-13: 9780763740634); Kendrew et al. (eds.), The Encyclopedia of Molecular Biology, published by Blackwell Science Ltd., 1994 (ISBN 0-632-02182-9); and Robert A. Meyers (ed.), Molecular Biology and Biotechnology: a Comprehensive Desk Reference, published by VCH Publishers, Inc., 1995 (ISBN 1-56081-569-8). Further, unless otherwise required by context, singular terms shall include pluralities and plural terms shall include the singular.

Unless otherwise stated, the various embodiments of the disclosure can be performed using standard procedures known to one skilled in the art, for example, in Maniatis et al., Molecular Cloning: A Laboratory Manual, Cold Spring Harbor Laboratory Press, Cold Spring Harbor, N.Y., USA (1982); Sambrook et al., Molecular Cloning: A Laboratory Manual (2 ed.), Cold Spring Harbor Laboratory Press, Cold Spring Harbor, N.Y., USA (1989); Davis et al., Basic Methods in Molecular Biology, Elsevier Science Publishing, Inc., New York, USA (1986); Current Protocols in Molecular Biology (CPMB) (Fred M. Ausubel, et al. ed., John Wiley and Sons, Inc.), Current Protocols in Immunology (CPI) (John E. Coligan, et. al., ed. John Wiley and Sons, Inc.), Current Protocols in Cell Biology (CPCB) (Juan S. Bonifacino et. al. ed., John Wiley and Sons, Inc.), which are all herein incorporated by reference in their entireties.

It should be understood that various embodiments of the disclosure are not limited to the particular methodology, protocols, and reagents, etc., described herein and as such may vary. The terminology used herein is for the purpose of describing particular embodiments only, and is not intended to limit the scope of the present technology, which is defined solely by the claims.

Other than in the operating examples, or where otherwise indicated, all numbers expressing quantities of ingredients or reaction conditions used herein should be understood as modified in all instances by the term “about.” The term “about” when used in connection with percentages will mean±1%.

All patents and publications identified are expressly incorporated herein by reference for the purpose of describing and disclosing, for example, the methodologies described in such publications that might be used in connection with the present technology. These publications are provided solely for their disclosure prior to the filing date of the present application. Nothing in this regard should be construed as an admission that the inventors are not entitled to antedate such disclosure by virtue of prior technology or for any other reason. All statements as to the date or representation as to the contents of these documents is based on the information available to the applicants and does not constitute any admission as to the correctness of the dates or contents of these documents.

Embodiments of this disclosure are based on the discovery of specific genetic mutations that are associated with malignant pleural mesothelioma (MPM) (see Tables 1 and 2, and FIG. 1). Their presences are indicators or biomarkers of the presence of the disease as well as status of the disease in a subject. Accordingly, the presence or absence of these gene mutations has utility related to the diagnosis, subtyping, prognosis and treatment of MPM. Thus, these biomarkers are useful for early diagnosis of malignant mesothelioma (MM), particularly MPM which make up the majority of MM in humans. In addition, these biomarkers are useful for generating a new classification of MM subtypes, for subtyping of new MM patients based on the described new MM subtype classification, for selecting and monitoring optimal treatment regimens based on the described new MM subtype classification, for monitoring MM patient treatment prognosis and outcome, and for the treatment of MM. The genes that are mutated are therapeutic targets.

In one embodiment, provided herein is a method for early detection of MM in a subject by looking for the presence of the disclosed mutations. For example, a mutation in a tumor necrosis factor receptor superfamily member 1A (TNFRSF1A) gene. For example, detecting for the presence of a G→A missence mutation at position 6439791 on chromosome 12 that results in a predicted R→W point mutation in the coded polypeptide. Alternatively, detecting for the presence of a A→G at 113 base pair (bp) from ATG start codon of the mRNA results in a predicted E→G point mutation at codon position 38 of the coded polypeptide; detecting for the presence of a A→G at 268 bp from ATG resulting in T→A point mutation at codon position 90 of the coded polypeptide; and/or detecting for the presence of a C→T at 712 bp from ATG resulting in R→W point mutation at codon position 238 of the coded polypeptide. See FIG. 1.

In one embodiment, the disclosure herein provides a method for surveillance for malignant mesothelioma (MM) in a subject comprising: (a) detecting the presence of at least one genetic mutation listed in Tables 1 and 2 in a biological sample obtained from the subject; and (b) subjecting the subject to at least one addition diagnostic test selected from the group consisting of chest X-ray, MRI, CT scan, PET scan, thoracentesis, mediastinoscopy, echocardiogram and thoracoscopy when at least one mutation is detected. In one embodiment, the MM is malignant pleural mesothelioma (MPM). In one embodiment, the mutation is not one that is listed on Table 2.

In one embodiment, the disclosure herein provides a method for surveillance for MM or early diagnosis in a subject comprising: (a) detecting the presence of at least one genetic mutation in a tumor necrosis factor receptor superfamily member 1A (TNFRSF1A) gene in a biological sample obtained from the subject; and (b) subjecting the subject to at least one addition diagnostic test selected from the group consisting of chest X-ray, MRI, CT scan, PET scan, thoracentesis, mediastinoscopy, echocardiogram and thoracoscopy when at least one mutation is detected. In one embodiment, the TNFRSF1A gene is a human gene, Gene ID: 7132, on chromosome 12p13.2, at 6437923 to 6451283, complement strand. In one embodiment, the at least one genetic mutation in the TNFRSF1A gene is selected from a A→G at 113 base pair (bp) from the ATG start codon of a mRNA; a A→G at 268 bp from ATG, and a C→T at 712 bp from ATG. In some embodiments, the presence of more than one genetic mutation is surveyed, for example, the presence of two or all three mutations of TNFRSF1A are surveyed.

In one embodiment, the MM is malignant pleural mesothelioma (MPM).

MPM is an aggressive cancer. Often symptoms do not arise until more advanced stages of cancer where curative surgery is no longer an option. Early detection provides a higher chance of successful therapeutic intervention such as surgery, chemotherapy, immunotherapy, radiation, gene therapy, photodynamic therapy and even personalized medical therapy before the cancer has metastasized to a point where any therapeutic intervention other than palliative care is no longer a valid option.

In some embodiments, the presence of more than one genetic mutation is surveyed, for example, two, three, four, five, six, seven, eight, nine, or ten genetic mutations disclosed in Tables 1 and 2 are surveyed.

In one embodiment, the subject is a human who is at risk of developing MM, particularly MPM. For example, the occupation of the subject, in past and present years, could have increased the subjects' risk of developing MPM, for example, construction, renovation or shipbuilding. Non-limiting exemplary works that are identified as associated with potential risk of developing MPM are: bricklayer, carpenters, automotive mechanics, boiler maker, insulator, electricity, labor, iron workers, merchant marines, painters, plumbers and plaster.

There are many possible risk factors that increase the risk of developing MPM. Non-limiting factors include personal history of asbestos exposure, living with someone who works with asbestos, prior polio vaccination that comprises a monkey virus, radiation, and family history.

A skill doctor can evaluate the level and severity of risk factors by obtaining a full medical history and presenting mesothelioma symptoms. The doctor will consider among other things, where asbestos exposure occurred, the length of exposure and the amount of asbestos that the subject was exposed to.

In one embodiment, the subject is a human.

In one embodiment, the subject has not been differentially diagnosed with MM, in particular, MPM.

In one embodiment, the subject is male. In another embodiment, the subject is female.

In one embodiment, the subject is between the ages of 35-95. In other embodiments, the subject is between the ages of 35-45, 35-55, 35-65, 35-75, 35-85, 35-80, 45-55, 45-65, 45-75, 45-85, 45-90, 45-95, 55-65, 55-75, 55-85, 55-95, 65-75, 65-85, 65-95, 75-85, 75-95 and 85-95, including all possible ranges between the ages of 35-95.

In one embodiment, the subject is 50 years and older. In other embodiments, the subject is 35 years and older, 40 years and older, or 60 years and older.

In one embodiment, the subject has prior exposure to asbestos.

In some embodiments, the subject lives or has lived with a person who works with asbestos or had prior exposure to asbestos. In other embodiments, the subject does not live or has not lived with a person who works with asbestos or had prior exposure to asbestos.

In one embodiment, the subject has no known prior exposure to asbestos.

In some embodiments, the subject has or has not exhibit any symptoms associated with MPM or any known lung diseases or disorders.

In one embodiment, the subject has exhibited at least one common respiratory ailment that is known.

In another embodiment, the subject has not exhibited any common respiratory ailment that is known.

Non-limiting common respiratory ailments that are known include chronic obstructive pulmonary disease (COPD), asthma, bronchitis, common cold, sinusitis, congestion, lung cancer, pneumonia, emphysemapulmonary tuberculosis (TB), cystic fibrosis, diffuse interstitial diseases (alveolitis) and pneumothorax.

In one embodiment, the subject is asymptomatic for a common respiratory ailment.

In one embodiment, the subject has not exhibited any symptom selected from the group anemia, blood clotting disorder, bowel obstruction, chest pain, persistent dry or raspy cough, coughing up blood (hemoptysis), shortness of breath (dyspnea), pain in the lower back or rib area, painful breathing, development of lumps under the skin on the chest, difficulty with swallowing (dysphagia), night sweats or fever, nausea, unexplained weight loss, fatigue, abdomen, pericardium, peritoneal and/or pleural effusion.

In another embodiment, the subject has at least one symptom selected from the group consisting of anemia, a blood clotting disorder, bowel obstruction, chest pain, persistent dry or raspy cough, coughing up blood (hemoptysis), shortness of breath (dyspnea), pain in the lower back or rib area, painful breathing, development of lumps under the skin on the chest, difficulty with swallowing (dysphagia), night sweats or fever, nausea, unexplained weight loss, fatigue, abdomen, pericardium, peritoneal and/or pleural effusion.

The method of early detection comprises routine and/or regular surveillance of the subject for presence of at least one mutation disclosed in Tables 1 and 2, and FIG. 1. The regular surveillance comprises take a biological sample, e.g., a blood sample, from the subject, for example, during an annual physical examination. For a subject who has positive or suspected prior asbestos exposure, or lives with someone who works with asbestos or had asbestos exposure in the past, then surveillance should be more frequent, e.g., every three months and also every time the subject visits the doctor's office. Similarly, surveillance should be more frequent if the subject is older than 35 years old.

In one embodiment, the detection of genetic mutations disclosed in Tables 1 and 2 and FIG. 1 comprises providing the biological sample obtained from the subject; extracting or isolating the nucleic acid from the biological sample; and analyzing for the presence of at least one mutation disclosed in Tables 1 and 2, and/or analyzing for the presence of at least one mutation disclosed for the TNFRSF1A gene. In another embodiment, the detection of genetic mutations described herein does not require extracting or isolating DNA from the biological sample. Typically, RT-PCR can be performed with lyates of the biological samples directly without extracting or isolating nucleic acid (e.g., DNA). Such techniques are common and known in the art.

In some embodiments, the biological sample include blood samples, plasma, serum, urine, sweat, peritoneal fluid sample, pleural fluid, bone marrow, cerebrospinal fluid and pericardial fluid and any tissue sample of the body. As used herein, a “tissue sample” refers to a portion, piece, part, mutation, or fraction of a tissue which is obtained or removed from an intact tissue of a subject, preferably a human subject. In one embodiment, the tissue sample is a blood sample. In another embodiment, the tissue sample is a peritoneal fluid sample.

In one embodiment, the tissue sample is obtained from a biopsy procedure in the subject. In one embodiment, the tissue sample is a tissue sample. In another embodiment, the tissue sample is obtained from a surgical procedure to remove a tumor mass from the subject.

As used herein, a “tumor sample” refers to a portion, piece, part, mutation, or fraction of a tumor, for example, a tumor which is obtained or removed from a subject (e.g., removed or extracted from a tissue of a subject), preferably a human subject.

The biological sample is collected by any method known in the art. For example, when the biological sample is a blood sample, the blood sample is collected from a peripheral vein of the subject.

In the embodiment where the biological sample is a blood sample, cells in the blood samples are harvested by any method known in the art, e.g., by centrifugation. Then the nucleic acid (e.g., DNA or RNA) therein is isolated and analyzed for the mutation disclosed in Tables 1 and 2, or TNFRSF1A gene mutations by any method known in the art. In another embodiment, the nucleic acid need not be isolated for analysis.

Alternatively, the nucleic acid therein is isolated from the whole blood or other biological samples, and analyzed for the mutations

Methods of nucleic acid isolation are well known in the art. Accordingly, the nucleic acid of biological samples can be isolated be any method known in the art. Commercially available DNA-isolation-kits e.g., from Roche, can also be used.

Methods of detecting gene mutation are also well known in the art. Accordingly, the mutations set forth in Tables 1 and 2, and the disclosed TNFRSF1A gene mutations can be detected by any method known in the art, e.g., by qRT-PCR followed by a DNA microarray chip hybridization or by DNA sequencing or by fluorescence in situ hybridization (FISH). See “Genetics 101: detecting mutations in human genes” in CMAJ (2002) 167:275-279.

Once the at least one mutation disclosed in Tables 1 and 2, or a disclosed TNFRSF1A mutation has been detected in the biological sample, e.g., a blood sample, a biological blood sample can be obtained from the subject and analyzed to confirm the finding of that mutation. Following confirmation, the subject is then subjected to at least one addition test to detect and/or confirm presence of MM before a treatment plan is implemented.

Alternatively, the subject is subjected to at least one addition test to detect and/or confirm presence of MM without a second biological sample to confirm the detection of the presence to the mutation.

Alternatively, a treatment plan is implemented for the subject without a second biological sample to confirm the detection of the presence to the mutation.

Non-limited examples of at least one addition diagnostic test include imaging test such as chest X-ray, magnetic resonance image (MRI), computer tomography scan (CT scan), positron emission tomography (PET scan); biopsy test such as mediastinoscopy, thoracentesis and thoracoscopy; and other tests such as echocardiogram.

In some embodiments, the method comprises detecting at least two, at least three, at least four, at least five, at least six, at least seven, at least eight, at least nine, at least ten mutation disclosed in Tables 1 and 2.

In one embodiment, the method comprises detecting the number of mutations that have been characterized for each subtype determined by the method described herein. For example, if subtype A of MM or MPM is characterized by mutations in the ten gene loci disclosed in Tables 1 and 2, and in disclosed TNFRSF1A mutations, e.g., in hypothetical genes ezv, mti, bci, cag, tpl, oo, bb, lno, xct, and wmi, then the method comprises detecting genetic mutations at these genes at the specific loci disclosed in Tables 1 and 2, and disclosed TNFRSF1A mutations.

In one embodiment, the method further comprises detecting for the presences of all the mutations disclosed in Tables 1 and 2, and disclosed TNFRSF1A mutations to generate a profile of gene mutations for the subject. This profile of gene mutations is then used to categorize the subject into one of the subtypes of MM generated by the method described herein.

In one embodiment when at least one mutation is detected in the biological sample from the subject, the method further comprising assigning a subtype of MM to the subject based the profile of gene mutations.

In one embodiment, the profile of gene mutations used for subtyping is obtained prior to any treatment.

In one embodiment when at least one mutation is detected in the biological sample from the subject, the method further comprises inputting the profile of gene mutations into a computer system equipped with a computer software for analyzing the profile of gene mutations and assigning a subtype of MM to the inputted profile of gene mutations.

In one embodiment, provided herein is a method of classifying subtypes of MM based on profiles of genetic mutations in a population of subjects having MPM. In one embodiment, the MM is MPM.

In one embodiment, the disclosure herein provides a method of classifying MM into subtypes based on profiles of genetic mutations in a population of subjects having MM comprising: (a) providing a genetic mutation profile database comprising at least three profiles of genetic mutation of the genes of Tables 1 and 2 at the specific location indicated in Tables 1 and 2, wherein the profiles are derived from a population of subjects having MM, and wherein the profiles are from biological samples obtained from the subjects prior to any treatment in order to create; (b) applying the genetic mutation database to a clustering algorithm which analyzes and identifies at least two separate and distinct clusters within the database, wherein each cluster comprising a unique collection of genetic mutations disclosed in Tables 1 and 2; (c) sorting the population of subjects having MM into the at least two separate and distinct clusters identified by the clustering algorithm; (d) monitoring the treatment regimen and prognosis of the subjects separated into the clusters of step (c); correlating the treatment regimen and prognosis of the subjects with the subject's designated cluster; (e) determining which treatment regimen for each cluster result in at least 2 fold increase in survival over the median survival time; and (f) associating the treatment regimen of step (g) with the respective cluster to form a subtype. In one embodiment, the population of subjects has MPM.

In one embodiment, the profile of genetic mutation is obtained by providing a biological sample from each subject of the population; extracting the nucleic acid from the biological sample; and analyzing for the presence of all the genetic mutations disclosed in Tables 1 and 2.

In one embodiment, wherein clustering step (b) and sorting step (c) are performed using a computer system equipped with a clustering algorithm for analyzing the profiles of gene mutations and assigning a subtype of MPM to the profile of gene mutations. For example, k-means algorithm. Cluster analysis or clustering is the task of assigning a set of objects into groups (called clusters) so that the objects in the same cluster are more similar (in some sense or another) to each other than to those in other clusters.

Methods of cluster analysis are well known in the art. Accordingly, a skilled artisan can cluster analyse the database of genetic mutation profiles by any method known in the art, e.g., any centroid-based clustering such as k-means algorithm, or distribution-based clustering, density-based clustering and pattern-based clustering.

To generate the required database, a population of human subjects who have been differentially diagnosed with MPM are identified. Biological samples such as blood samples are obtained from these subjects prior to and during the course of treatment. The treatment regime(s) and prognosis, and survival of each subject are recorded. Biological samples are obtained at several time points during treatment, e.g., at a first time and at least a second time during treatment, wherein the first time is an earlier time point than the second time, that is, the first and second time points are in chronological order. The genetic mutation profiles of the genes and the specific type of mutations disclosed in Tables 1 and 2, and those disclosed for TNFRSF1A are analyzed for all the biological samples collected to create several data sets of genetic mutation profiles, one data set for prior to treatment, and at least one for during one course of treatment, for example, after 2 months of treatment. Each sampling at a particular time point during treatment generates a data set of gene mutation profiles for that time points. For example, if there are two points sampling after start of treatment, then there are two data sets of gene mutation profiles, one data set for each sampling time points. The collection of data sets of forms a database of gene mutation profiles for generating the subtypes of MPM.

The treatment regime(s) and prognosis, and length of survival of the subjects are monitored throughout until death of the subject.

In one embodiment, the genetic mutation profiles obtained prior to treatment is used to generate at least two separate and distinct subtypes of MPM among the subjects using a clustering algorithm. The genetic mutation profiles obtained prior to treatment are applied to a clustering algorithm to identify at least two separate and distinct groups among the profiles, e.g, subtype A and subtype B. Each subtype comprises a particular collection of genetic mutations derived from those disclosed in Table 1. Accordingly, each identified MPM subtype has a specific gene mutation profile. For example, subtype A is characterized by ten different genetic mutations derived from those disclosed in Table 1 and subtype B is characterized by twelve different genetic mutations derived from those disclosed in Table 1. There can be some overlap of genetic mutations comprising the subtypes classified by the method described herein. For example, subtype A has mutations at the hypothetical genes ezv, mti, bci, cag, tpl, oo, bb, lno, xct, and wmi; and subtype B has mutations at hypothetical genes ezv, mti, bci, cag, gbb, rmi, uugc, lhr, gus, moor, atc, and arg; then genes ezv, mti, bci, and cag are genes with common genetic mutations of subtypes A and B. In another embodiment, there is no overlap of genetic mutations comprising the subtypes classified by the method described herein.

Then for each subject in the population, the subject would be assign a subtype based on his or her profile of gene mutations obtained prior to treatment.

Then the treatment regime(s) and prognosis, and survival of each subject are correlated with the subtype assigned to the subject based on the subject's genetic mutation profile obtained prior to treatment. Following that is to determine which treatment regimen for each subtype results in at least 2 fold increase in survival over the median survival time. The median survival time is nine months after diagnosis. For each subtype, the treatment regimen that gives a subject at least 2 fold increase in survival time over the median is then selected and associated with that subtype. In some embodiments, the increase in survival time is at least three, at least four, at least five, or up to at least six over the median is then selected and associated with that subtype.

In one embodiment, the median survival time that is associated with a particular subtype is the average survival time of all subjects assigned to that subtype regardless of the treatment regime.

For example, subjects who are designated subtype A survived for 30 months from confirmatory diagnosis when the subjects were treated with a new chemotherapy drug like ALIMTA® compared to similarly designated subtype A subjects who lived for only 10 months when treated with ALIMTA® and radiation. Therefore, chemotherapy treatment with ALIMTA® and without radiation is associated with a better outcome in subtype A subjects. Using this information, for a newly diagnosed patient, a doctor can first subtype the MM in the patient, and based on the patient's subtype, prescribe a recommended therapy for the patient's subtype of MM.

The treatment regime(s) and prognosis, and survival of the subjects are also correlated with the genetic mutation profile during treatment for the particular collection of genetic mutations specific to each subtype. It is contemplated that an effective treatment regime(s) would reduce the number of mutations during the course of treatment for the particular collection of genetic mutations characterized and monitored for each subtype. It is also contemplated that when treatment is ineffective, there would be no change in the number of mutations during the course of treatment or an increase in the number of mutations during the course of treatment when the some of the mutations were absent previously during prior to treatment or absent previously during treatment, i.e., had disappeared below detectable levels during the earlier periods of treatment but have now resurface, indicating resurgence of the cancer and that the treatment is no longer effective.

Accordingly, the doctor can determine whether a treatment is effective by monitoring the changes in the number of mutations for the particular collection of genetic mutations comprising each subtype during the course of treatment.

In addition, the genetic mutation profiles obtained after the end of a treatment regime can be used to correlate subtypes with rate of recurrence of the disease.

In one embodiment, the surveillance method described herein is also useful for surveying for recurrence of the disease after completion of one or more courses of treatment. For example, prior to treatment and after confirmation of MM or MPM diagnosis, the subject has a genetic mutation profile comprising ten mutations characteristic of subtype B. After one or more courses of treatment, the subject's profile now has only one mutation characteristic of subtype B. All treatment is then terminated. Then throughout the next year, for every three months, a biological sample is obtained from the subject and a genetic mutation profile is produced and compared to those for subtype B. When the profile accrues about 30% of the mutations of subtype B, i.e., an additional three mutations over the single mutation when treatment was terminated for this hypothetical example, the subject is deemed to have relapse. The subject now has four mutations characteristic of subtype B. The time it took to relapse is recorded and correlated with the assigned subtype and also the treatment. This correlation will provide a method of predicting recurrence of the disease after remission or completion of a particular treatment regime wherein the treatment was deemed effective by a reduction of the number of genetic mutations in a biological sample obtained during treatment. The reduction is at least 10% compared to the total number of genetic mutations characteristic of the assigned subtype. In some embodiments, the reduction is at least 15%, at least 20%, at least 25%, at least 30%, at least 35%, at least 40%, at least 45%, at least 50%, at least 55%, at least 60%, at least 65%, at least 70%, at least 75%, at least 80%, at least 85%, at least 90%, at least 95%, at least 99%, at least 100%, including all the integer percent between 10% to 100%.

For example, a subject who is assigned subtype A is treated with chemotherapy drugs carboplatin and cisplatin, and relapsed about 5 month after the treatment was stopped because treatment was effective by way of a reduction of the number of genetic mutations characteristic of the subtype A to zero. Another subject who is also assigned subtype A is treated with chemotherapy drugs onconase and gemcitabine, and relapsed about 10 month after the treatment was stopped. This subject also had complete reduction of the number of genetic mutations characteristic of the subtype A. Thus, for subtype A of MM, treatment with onconase and gemcitabine gives longer cancer free period before relapse.

In one embodiment, provided herein is a method of classifying MPM in subjects into subtypes based on the genetic mutation profiles of the genes disclosed in Tables 1 and 2, and a TNFRSF1A mutation. It is contemplated that by classifying MPM into subtypes, it would allow the doctor to tailor treatment that is effective for each subtype. This would provide better and effective treatment and prognosis overall for the subject.

In one embodiment, the disclosure herein provides a method of subtyping MM in a subject comprising: (a) detecting for the presences of all the mutations disclosed in Tables 1 and 2, and disclosed TNFRSF1A mutations to generate a profile of gene mutations; (b) comparing the profile of gene mutations with a collection of genetic mutations associated with each subtypes identified in the method described herein; and (c) assigning a subtype of MM when the profile of gene mutations of the subject matches the collection by at least a 70 percentile. In other embodiments, when the profile of gene mutations of the subject matches the collection characteristic of a subtype by at least 75%, at least 80%, at least 85%, at least 90%, at least 95%, at least 99%, at least 100%, including all the integer percent between 70% to 100%.

In one embodiment, the subject has MPM.

In one embodiment, the profile of genetic mutation is produced by providing a biological sample from a subject; extracting or isolating the nucleic acid from the biological sample; and analyzing for the presence of all the genetic mutations disclosed in Tables 1 and 2, and the disclosed TNFRSF1A mutations.

In other embodiments of all methods described herein, the profile of genetic mutations is obtained without having to isolate or extract the nucleic acid from the biological sample.

In one embodiment, the comparing step (b) and assigning step (c) are performed using a computer system equipped with a clustering algorithm for analyzing the profiles of gene mutations and assigning a subtype of MM to the profile of gene mutations.

When a subject is suspected of having MM, MPM or has been diagnosed by any method known in the art or by the surveillance or early detection method described herein, a biological sample is obtained from the subject. From the biological sample, a profile of genetic mutation of the genes of Tables 1 and 2, and the disclosed TNFRSF1A mutations. This genetic mutation profile is then compared with those of the subtypes of MM generated by the method described herein. When the subject's profile is at least 70 percentile matches that of a MPM subtype, the subject is then assigned that subtype. For example, subtype A is characterized by the collection of mutations at the hypothetical genes ezv, mti, bci, cag, tpl, oo, bb, lno, xct, and wmi; and subtype B is characterized by the collection of mutations at the hypothetical genes ezv, mti, bci, cag, gbb, rmi, uugc, lhr, gus, moor, atc, and arg. If a subject now has a genetic mutation profile with mutations at the hypothetical genes ezv, mti, bci, cag, tpl, oo, bb, lno, xct, rmi, uugc, lhr, and gus, the subject's profile matches nine out of ten mutations characteristic of subtype A but only four out of twelve mutations characteristic of subtype B. Therefore, the subject will be assign to subtype A and will be given subtype A treatment protocol.

Accordingly, in one embodiment, the treatment of a subject is dictated by the subtype of MM the subject has.

In one embodiment, the disclosure herein provides a method for monitoring the progression or regression of a subject having MM, the method comprising: (a) monitoring the presence or absence of at least one genetic mutation listed in Tables 1 and 2, and disclosed TNFRSF1A mutations or listed in a collection of gene mutations characteristic of a subtype of MM in a biological sample from the subject prior to start of a treatment or at a first time during the course of a treatment; (b) monitoring the presence or absence of the at least one genetic mutation listed in Tables 1 and 2, and disclosed TNFRSF1A mutations or listed in a collection of gene mutations characteristic of a subtype of MM in another biological sample from the subject at a second time during the course of a treatment, wherein the first and second time are in chronological order, and wherein the same genetic mutation(s) is monitored at in step (a) and step (b); and comparing the first measurement and the second measurement, wherein the comparative measurements indicates the course of MM in the subject and also indicates the treatment plan moving forward. In one embodiment, the subject has MM.

In one embodiment, there is no disappearance of the at least one genetic mutation during the course of treatment when the at least one genetic mutation is present prior to start of treatment or at the first time indicating progression of MM. The observation that there is no disappearance of the at least one genetic mutation during the course of treatment indicates that the treatment is not effective and terminating the treatment is recommended.

In one embodiment, wherein there is appearance of the at least one genetic mutation during the course of treatment when the at least one genetic mutation is absent prior to start of treatment or at the first time indicating progression of MM. The observation that there is additional genetic mutation surfacing during the course of treatment indicates that the treatment is not effective and terminating the treatment is recommended.

In one embodiment, wherein there is disappearance of the at least one genetic mutation during the course of treatment, when the at least one genetic mutation is present prior to start of treatment or at the first time indicating regression of MM. The observation that there is disappearance of the at least one genetic mutation during the course of treatment indicates that treatment is effective and continuing the treatment is recommended.

In one embodiment, the method further comprises commencing another treatment when current treatment is terminated.

In one embodiment, the collection of gene mutations characteristic of a subtype of MM is determined by the method of classifying MM subtypes as described herein.

In one embodiment, the subject is identified as having a subtype of MM by the method of subtyping MM as described herein.

In one embodiment of any one of the methods described herein, the method does not comprise detecting any one or more of the genetic mutations disclosed in Table 2.

In one embodiment of any one of the methods described herein, the method does not comprise detecting the presence of a genetic mutation in a gene selected from the group consisting of ACTRA1A, MSRA5, PDZK1IP1, PSMD13, UQCRC1, COL5A2, XRCC6, LRP10, MPM2/C14orf159, TM9SF1, PARF/C9orf86, AVEN, PSMD8BP1/NOB1, MPM1/CXorf34, and FLJ00312/CTGLF6.

In one embodiment of any one of the methods described herein, the method comprises detecting at least one genetic mutation of the TNFRSF1A disclosed in FIG. 1.

In one embodiment of any one of the methods described herein, the method comprises detecting at least two genetic mutation of the TNFRSF1A disclosed in FIG. 1.

In one embodiment of any one of the methods described herein, the method comprises detecting all three genetic mutation of the TNFRSF1A disclosed in FIG. 1.

In one embodiment, the disclosure herein provides a method for treating MM in a subject comprising: (a) categorizing the MM to a subtype according to the method of subtyping MM as described herein; and administering an effective treatment regime to the subject based on the subtype.

In one embodiment, the disclosure herein provides a method for treating MM in a subject comprising administering to a subject in need thereof a therapeutically effective amount of an agent that increases the expression of a tumor necrosis factor receptor superfamily member 1A (TNFRSF1A).

In one embodiment, the disclosure herein provides a method for treating MM in a subject comprising administering to a subject in need thereof a composition comprising an agent that increases the expression of a tumor necrosis factor receptor superfamily member 1A (TNFRSF1A). In one embodiment, the composition further comprises a pharmaceutically acceptable carrier.

In one embodiment, the disclosure herein provides a composition comprising an agent that increases the expression of a tumor necrosis factor receptor superfamily member 1A (TNFRSF1A) gene for use in the treatment of MM.

In one embodiment, the disclosure herein provides a use of an agent that increases the expression of a tumor necrosis factor receptor superfamily member 1A (TNFRSF1A) gene for the treatment of MM.

TNFRSF1A (akaCD120a) is one of the most primary receptors for the tumor necrosis factor-alpha. It has been shown to be localized to both plasma membrane lipid rafts and the trans golgi complex with the help of the death domain (DD). TNFRSF1A can activate the transcription factor NF-κB, mediate apoptosis, and regulate inflammation processes.

Mutations of the TNFRSF1A gene lead to a complete and/or partial suppression of gene expression or modified protein. TNFRSF1A codes for a critical receptor for TNF that allows TNF to mediate apoptotic response. Deficiency or defective receptor prevents apoptosis of the cancers comprising mesothelioma. Accordingly, increasing overall TNFRSF1A gene expression can help to induce apoptosis of the cancer cells.

As used herein, “an agent that increases TNFRSF1A expression” is a drug, a compound, a chemical, or a formulation that increases overall TNFRSF1A gene expression in a subject. In other embodiments, “an agent that increases TNFRSF1A expression” is a nucleic acid sequence coding for a TNFRSF1A coding sequence or a vector or DNA construct comprising a nucleic acid sequence coding for a TNFRSF1A.

In some embodiment, the agent is thalidomide or lenalidomide (levlimid).

In one embodiment, the agent is a nucleic acid sequence comprising the human sequence TNFRSF1A mRNA sequence NM_(—)001065.2.

In one embodiment, the agent is a nucleic acid sequence comprising the sequence

(SEQ. ID. NO: 1) :atgggcc tctccaccgt gcctgacctg ctgctgccac tggtgctcct ggagctgttg gtgggaatat  acccctcagg ggttattgga ctggtccctc acctagggga cagggagaag agagatagtg tgtgtcccca  aggaaaatat atccaccctc aaaataattc gatttgctgt accaagtgcc acaaaggaac ctacttgtac aatgactgtc caggcccggg gcaggatacg gactgcaggg agtgtgagag cggctccttc accgcttcag aaaaccacct cagacactgc ctcagctgct ccaaatgccg aaaggaaatg ggtcaggtgg agatctcttc  ttgcacagtg gaccgggaca ccgtgtgtgg ctgcaggaag aaccagtacc ggcattattg gagtgaaaac cttttccagt gcttcaattg cagcctctgc ctcaatggga ccgtgcacct ctcctgccag gagaaacaga acaccgtgtg cacctgccat gcaggtttct ttctaagaga aaacgagtgt gtctcctgta gtaactgtaa gaaaagcctg gagtgcacga agttgtgcct accccagatt gagaatgtta agggcactga ggactcaggc accacagtgc tgttgcccct ggtcattttc tttggtcttt gccttttatc cctcctcttc attggtttaa  tgtatcgcta ccaacggtgg aagtccaagc tctactccat tgtttgtggg aaatcgacac ctgaaaaaga gggggagctt gaaggaacta ctactaagcc cctggcccca aacccaagct tcagtcccac tccaggcttc acccccaccc tgggcttcag tcccgtgccc agttccacct tcacctccag ctccacctat acccccggtg actgtcccaa ctttgcggct ccccgcagag aggtggcacc accctatcag ggggctgacc ccatccttgc  gacagccctc gcctccgacc ccatccccaa cccccttcag aagtgggagg acagcgccca caagccacag agcctagaca ctgatgaccc cgcgacgctg tacgccgtgg tggagaacgt gcccccgttg cgctggaagg aattcgtgcg gcgcctaggg ctgagcgacc acgagatcga tcggctggag ctgcagaacg ggcgctgcct gcgcgaggcg caatacagca tgctggcgac ctggaggcgg cgcacgccgc ggcgcgaggc cacgctggag ctgctgggac gcgtgctccg cgacatggac ctgctgggct gcctggagga catcgaggag gcgctttgcg  gccccgccgc cctcccgccc gcgcccagtc ttctcagatg aggctgcgcc cctgcgggca gctctaagga ccgtcctgcg agatcgcctt ccaaccccac ttttttctgg aaaggagggg tcctgcaggg gcaagcagga gctagcagcc gcctacttgg tgctaacccc tcgatgtaca tagcttttct cagctgcctg cgcgccgccg acagtcagcg ctgtgcgcgc ggagagaggt gcgccgtggg ctcaagagcc tgagtgggtg gtttgcgagg  atgagggacg ctatgcctca tgcccgtttt gggtgtcctc accagcaagg ctgctcgggg gcccctggtt  cgtccctgag cctttttcac agtgcataag cagttttttt tgtttttgtt ttgttttgtt ttgtttttaa atcaatcatg ttacactaat agaaacttgg cactcctgtg ccctctgcct ggacaagcac atagcaagct gaactgtcct aaggcagggg cgagcacgga acaatggggc cttcagctgg agctgtggac ttttgtacat  acactaaaatt ctgaagtta aagctctgct cttggaaaaa.

In one embodiment, the agent is a vector or DNA construct comprising a nucleic acid sequence described herein.

In some embodiments, the nucleic acid sequence is DNA or RNA.

In one embodiment, a vector comprising a nucleic acid sequence described herein is an expression vector. The expression vector can have a strong promoter sequence driving the expression of the TNFRSF1A transgene in the subject. Strong promoter sequences include but are not limited to the Moloney murine leukemia virus promoter, cytomegalovirus promoter, the simian virus 40 early region promoter, the lymphotropic papovavirus, and the human beta-globin gene promoter sequences. In one embodiment, the promoter can be chimeric sequences from several promoter types as described in U.S. Pat. No. 6,136,536 which is incorporated hereby reference in its entirety. In another embodiment, the promoter can be the human osteocalcin (hOC) promoter (McCarthy H. O., et. al., 2007, J. Gene Medicine, 9: 511-20).

In one embodiment of any method described, the DNA sequence that encodes a human TNFRSF1A transgene is in a vector. In one embodiment, the vector is an expression vector for the purpose of expressing a DNA sequence encoding a protein in a cell. In one embodiment, the vector is an inducible vector, such as a tetracycline inducible vector. Methods described, for example, in Wang et al. Proc. Natl. Acad. Sci. 100: 5103-5106, using pTet-On vectors (BD Biosciences Clontech, Palo Alto, Calif.) can be used. In some embodiments, a vector is a plasmid vector, a viral vector, or any other suitable vehicle adapted for the insertion and foreign sequence and for the introduction into eukaryotic cells. The vector can be an expression vector capable of directing the transcription of the DNA sequence encoding TNFRSF1A.

As used herein, a “TNFRSF1A transgene” is a TNFRSF1A coding sequence that has been transferred into a subject by any of a number of genetic engineering techniques known in the art.

In one embodiment, the expression vector is a viral vector such as an adenovirus, an adeno-associated virus, or lentivirus, for example, MDH.xdna murine retroviral vector. Viral vectors provide an additional advantage of ease of transfecting the host cell by viral infection. Viral expression vectors can be selected from a group comprising, for example, reteroviruses, lentiviruses, Epstein Barr virus-, bovine papilloma virus, adenovirus- and adeno-associated-based vectors or hybrid virus of any of the above.

In another embodiment, the expression in a non-viral vector. Such vectors can be transfected into host cells of the subject using known transfection methods known in the art, such as cationic lipid transfection.

In one embodiment, the vector is episomal. The use of a suitable episomal vector provides a means of maintaining the antagonist nucleic acid molecule in the subject in high copy number extra chromosomal DNA thereby eliminating potential effects of chromosomal integration.

Any methods known in the art can be for constructing a vector for the purpose of expressing a DNA sequence encoding a TNFRSF1A in a cell. For example, conventional polymerase chain reaction (PCR) cloning techniques can be used to clone the DNA sequence encoding a TNFRSF1A. A DNA sequence encoding a TNFRSF1A can be initially cloned into a general purpose cloning vector such as pUC19, pBR322, pBluescript vectors (STRATAGENE® Inc.) or pCR TOPO® from INVITROGEN™ Inc. prior to cloning into the expression vector.

Each PCR primer should have at least 15 nucleotides overlapping with its corresponding templates at the region to be amplified. The polymerase used in the PCR amplification should have high fidelity such as STRATAGENE®'s PFUULTRA™ polymerase for reducing sequence mistakes during the PCR amplification process. For ease of ligating several separate PCR fragments together, for example in the construction of a messenger DNA sequence encoding TNFRSF1A such as SEQ. ID. NO: 1, and subsequently inserting into a cloning vector, the PCR primers should also have distinct and unique restriction digestion sites on their flanking ends that do not anneal to the DNA template during PCR amplification. The choice of the restriction digestion sites for each pair of specific primers should be such that the DNA sequence encoding a TNFRSF1A is in-frame and will encode the predicted TNFRSF1A protein from beginning to end with no stop codons.

In gene therapy, a vector comprising a DNA sequence encoding a TNFRSF1A includes but is not limited to adenovirus, retrovirus, lentivirus, adeno associated virus, envelope protein pseudotype virus (chimeric virus), and virosomes (e.g. liposomes combined with an inactivated HIV or influenza virus).

A simplified system for generating recombinant adenoviruses is presented by He T C. et al. Proc. Natl. Acad. Sci. USA 95:2509-2514, 1998. The gene of interest is first cloned into a shuttle vector, e.g., pAdTrack-CMV. The resultant plasmid is linearized by digesting with restriction endonuclease Pme I, and subsequently cotransformed into E. coli. BJ5183 cells with an adenoviral backbone plasmid, e.g. pAdEasy-1 of STRATAGENE®'s AdEasy™ Adenoviral Vector System. Recombinant adenovirus vectors are selected for kanamycin resistance, and recombination confirmed by restriction endonuclease analyses. Finally, the linearized recombinant plasmid is transfected into adenovirus packaging cell lines, for example HEK 293 cells (E1-transformed human embryonic kidney cells) or 911 (E1-transformed human embryonic retinal cells) (Human Gene Therapy 7:215-222, 1996). Recombinant adenoviruses are generated within the HEK 293 cells.

Recombinant lentivirus has the advantage of delivery and expression of a TNFRSF1A in either dividing or non-dividing mammalian cells. The HIV-1 based lentivirus can effectively transduce a broader host range than the Moloney Leukemia Virus (MoMLV)-base retroviral systems. Preparation of the recombinant lentivirus can be achieved using the pLenti4/V5-DEST™, pLenti6/V5-DEST™ or pLenti vectors together with ViraPower™ Lentiviral Expression systems from INVITROGEN™.

An embodiment is the use of AAV viral vectors comprising nucleic acids encoding a TNFRSF1A. Recombinant adeno-associated virus (rAAV) vectors are applicable to a wide range of host cells including many different human and non-human cell lines or tissues. Because AAV is non-pathogenic and does not ellicit an immune response, a multitude of pre-clinical studies have reported excellent safety profiles. rAAVs are capable of transducing a broad range of cell types and transduction is not dependent on active host cell division. High titers, >108 viral particle/ml, are easily obtained in the supernatant and 1011-1012 viral particle/ml with further concentration. The transgene is integrated into the host genome so expression is long term and stable.

The use of alternative AAV serotypes other than AAV-2 (Davidson et al (2000), PNAS 97:3428-32; Passini et al (2003), J. Virol 77:7034-40) has demonstrated different cell tropisms and increased transduction capabilities. With respect to brain cancers, the development of novel injection techniques into the brain, specifically convection enhanced delivery (CED; Bobo et al (1994), PNAS 91:2076-80; Nguyen et al (2001), Neuroreport 12:1961-4), has significantly enhanced the ability to transduce large areas of the brain with an AAV vector.

Large scale preparation of AAV vectors is made by a three-plasmid cotransfection of a packaging cell line: AAV vector carrying the coding nucleic acid, AAV RC vector containing AAV rep and cap genes, and adenovirus helper plasmid pDF6, into 50×150 mm plates of sub-confluent 293 cells. Cells are harvested three days after transfection, and viruses are released by three freeze-thaw cycles or by sonication.

AAV vectors are then purified by two different methods depending on the serotype of the vector. AAV2 vector is purified by the single-step gravity-flow coluMM purification method based on its affinity for heparin (Auricchio, A., et. al., 2001, Human Gene therapy 12:71-6; Summerford, C. and R. Samulski, 1998, J. Virol. 72:1438-45; Summerford, C. and R. Samulski, 1999, Nat. Med. 5: 587-88). AAV2/1 and AAV2/5 vectors are currently purified by three sequential CsCl gradients.

In one embodiment, the method further comprises selecting a subject who is in need of treatment, such as one who has been diagnosed with MM.

In one embodiment, the subject has been diagnosed with MM.

In one embodiment, the diagnosis of MM is according to the method described herein.

In one embodiment, the subject having MM has been subtyped according to the method described herein.

In one embodiment of any treatment methods or any method described herein, the MM is MPM.

In one embodiment of any treatment method described herein, the method further comprises administering an additional cancer therapy, wherein the at least one additional cancer therapy is selected from the group consisting of radiation therapy, chemotherapy, immunotherapy and gene therapy.

In one embodiment of any treatment method described herein, the composition is administered in conjunction with at least one additional cancer therapy to achieve a combination cancer therapy.

In other embodiments of any treatment method described herein, the at least one additional cancer therapy is selected from the group consisting of growth inhibitory agents, cytotoxic agents, anti-angiogenesis agents, apoptotic agents, anti-tubulin agents, anti-CD20 antibodies, an epidermal growth factor receptor (EGFR) antagonist, a platelet derived growth factor inhibitor, a COX-2 inhibitor, an interferon, and a cytokine (e.g., G-CSF, granulocyte-colony stimulating factor).

In other embodiments of any treatment method described herein, the at least one additional cancer therapy is selected from the group consisting of 13-cis-retinoic acid, 2-CdA, 2-Chlorodeoxyadenosine, 5-Azacitidine, azacytidine, 5-Fluorouracil, 5-FU, 6-Mercaptopurine, 6-MP, 6-TG, 6-Thioguanine, abiraterone acetate, Abraxane, Accutane®, Actinomycin-D, Adriamycin®, Adrucil®, Afinitor®, Agrylin®, Ala-Cort®, Aldesleukin, Alemtuzumab, ALIMTA, Alitretinoin, Alkaban-AQ®, Alkeran®, All-transretinoic Acid, Alpha Interferon, Altretamine, Amethopterin, Amifostine, Aminoglutethimide, Anagrelide, Anandron®, Anastrozole, Arabinosylcytosine, Ara-C, Aranesp®, Aredia®, Arimidex®, Aromasin®, Arranon®, Arsenic Trioxide, Arzerra™, Asparaginase, ATRA, Avastin®, Axitinib, Azacitidine, BCG, BCNU, Bendamustine, Bevacizumab, Bexarotene, BEXXAR®, Bicalutamide, BiCNU, Blenoxane®, Bleomycin, Bortezomib, Busulfan, Busulfex®, C225, Cabazitaxel, Calcium Leucovorin, Campath® Camptosar® Camptothecin-11, Capecitabine, Caprelsa® Carac™ Carboplatin, Carmustine, Carmustine Wafer, Casodex®, CC-5013, CCI-779, CCNU, CDDP, CeeNU, Cerubidine®, Cetuximab, Chlorambucil, Cisplatin, Citrovorum Factor, Cladribine, Cortisone, Cosmegen®, CPT-11, Crizotinib, Cyclophosphamide, Cytadren®, Cytarabine, Cytarabine Liposomal, Cytosar-U®, Cytoxan®, Dacarbazine, Dacogen, Dactinomycin, Darbepoetin Alfa, Dasatinib, Daunomycin, Daunorubicin, Daunorubicin Hydrochloride, Daunorubicin Liposomal, DaunoXome®, Decadron, Decitabine, Delta-Cortef®, Deltasone®, Denileukin Diftitox, Denosumab, DepoCyt™, Dexamethasone, Dexamethasone Acetate, Dexamethasone Sodium Phosphate, Dexasone, Dexrazoxane, DHAD, DIC, Diodex, Docetaxel, Doxil®, Doxorubicin, Doxorubicin Liposomal, Droxia™, DTIC, DTIC-Dome®, Duralone®, Eculizumab, Efudex®, Eligard™, Ellence™, Eloxatin®, Elspar®, Emcyt®, Epirubicin, Epoetin Alpha, Erbitux, Eribulin, Erlotinib, Erwinia L-asparaginase, Estramustine, Ethyol, Etopophos®, Etoposide, Etoposide Phosphate, Eulexin®, Everolimus, Evista®, Exemestane, Fareston®, Faslodex®, Femara®, Filgrastim, Floxuridine, Fludara®, Fludarabine, Fluoroplex®, Fluorouracil, Fluorouracil (cream), Fluoxymesterone, Flutamide, Folinic Acid, FUDR®, Fulvestrant, Gefitinib, Gemcitabine, Gemtuzumab ozogamicin, Gemzar, Gleevec™, Gliadel® Wafer, Goserelin, Granulocyte-Colony Stimulating Factor (G-CSF), Granulocyte Macrophage Colony Stimulating Factor (GM-CSF), Halaven®, Halotestin®, Herceptin®, Hexadrol, Hexylen®, Hexamethylmelamine, HMM, Hycamtin®, Hydrea®, Hydrocort Acetate®, Hydrocortisone, Hydrocortisone Sodium Phosphate, Hydrocortisone Sodium Succinate, Hydrocortone Phosphate, Hydroxyurea, Ibritumomab, Ibritumomab Tiuxetan, Idamycin®, Idarubicin, Ifex®, IFN-alpha, Ifosfamide, IL-11, IL-2, Imatinib mesylate, Imidazole Carboxamide, Inlyta®, Interferon alpha, Interferon Alpha-2b (PEG Conjugate), Interleukin-2, Interleukin-11, Intron A® (interferon alpha-2b), Ipilimumab, Iressa®, Irinotecan, Isotretinoin, Ixabepilone, Ixempra™, Jevtana®, Kidrolase (t), Lanacort®, Lapatinib, L-asparaginase, LCR, Lenalidomide, Letrozole, Leucovorin, Leukeran, Leukine™, Leuprolide, Leurocristine, Leustatin™, Liposomal Ara-C, Liquid Pred®, Lomustine, L-PAM, L-Sarcolysin, Lupron®, Lupron Depot®, Matulane®, Maxidex, Mechlorethamine, Mechlorethamine Hydrochloride, Medralone®, Medrol®, Megace®, Megestrol, Megestrol Acetate, Melphalan, Mercaptopurine, Mesna, Mesnex™, Methotrexate, Methotrexate Sodium, Methylprednisolone, Meticorten®, Mitomycin, Mitomycin-C, Mitoxantrone, M-Prednisol®, MTC, MTX, Mustargen®, Mustine, Mutamycin®, Myleran®, Mylocel™, Mylotarg®, Navelbine®, Nelarabine, Neosar®, Neulasta™, Neumega®, Neupogen®, Nexavar®, Nilandron®, Nilotinib, Nilutamide, Nipent®, Nitrogen Mustard, Novaldex®, Novantrone®, Nplate, Octreotide, Octreotide acetate, Ofatumumab, Oncospar®, Oncovin®, Ontak®, Onxal™, Oprelvekin, Orapred®, Orasone®, Oxaliplatin, Paclitaxel, Paclitaxel Protein-bound, Pamidronate, Panitumumab, Panretin®, Paraplatin®, Pazopanib, Pediapred®, PEG Interferon, Pegaspargase, Pegfilgrastim, PEG-INTRON™, PEG-L-asparaginase, PEMETREXED, Pentostatin, Phenylalanine Mustard, Platinol®, Platinol-AQ®, Prednisolone, Prednisone, Prelone®, Procarbazine, PROCRIT®, Proleukin®, Prolia®, Prolifeprospan 20 with Carmustine Implant, Provenge®, Purinethol®, Raloxifene, Revlimid®, Rheumatrex®, Rituxan®, Rituximab, Roferon-A® (Interferon Alfa-2a), Romiplostim, Rubex®, Rubidomycin hydrochloride, Sandostatin®, Sandostatin LAR®, Sargramostim, Sipuleucel-T, Soliris®, Solu-Cortef®, Solu-Medrol®, Sorafenib, SPRYCEL™, STI-571, Streptozocin, SU11248, Sunitinib, Sutent®, Tamoxifen, Tarceva®, Targretin®, Tasigna®, Taxol®, Taxotere®, Temodar®, Temozolomide, Temsirolimus, Teniposide, TESPA, Thalidomide, Thalomid®, TheraCys®, Thioguanine, Thioguanine Tabloid®, Thiophosphoamide, Thioplex®, Thiotepa, TICE®, Toposar®, Topotecan, Toremifene, Torisel®, Tositumomab, Trastuzumab, Treanda®, Tretinoin, Trexall™, Trisenox®, TSPA, TYKERB®, Valrubicin, Valstar, vandetanib, VCR, Vectibix™, Velban®, Velcade®, Vemurafenib, VePesid®, Vesanoid®, Viadur™, Vidaza®, Vinblastine, Vinblastine Sulfate, Vincasar Pfs®, Vincristine, Vinorelbine, Vinorelbine tartrate, VLB, VM-26, Vorinostat, Votrient, VP-16, Vumon®, Xalkori capsules, Xeloda®, Xgeva®, Yervoy®, Zanosar®, Zelboraf, Zevalin™, Zinecard®, Zoladex®, Zoledronic acid, Zolinza, Zometa®, and Zytiga®.

In other embodiments of any treatment method described herein, the at least one additional cancer therapy is a mesothelioma cancer therapy.

In other embodiments of any treatment method described herein, the mesothelioma cancer therapy includes but is not limited to carboplatin, cisplatin, cyclophosphamide, doxorubicin, gemcitabine, navelbine, onconase, paclitaxel, pemetrexed, MORAb-009, SS1(dsFv)-PE38, and bevacizumab.

In one embodiment of any treatment method described herein, the method further comprises administering a drug that treats at least one symptom of cancer or cancer therapy. For example, for low blood count or anemia resulting from the chemo- or radiation therapy, erythropoietin can be administered to promote de novo the production of blood cell cells.

In one embodiment of any treatment method described herein, the agent or the composition is administered by a route selected from the group consisting of: intravenous, intramuscular, subcutaneous, intradermal, topical, intraperitoneal, intrathecal, intrapleural, intrasynovial, intrauterine, intravaginal, intratumor, and parenteral administration.

In one embodiment of any of the composition described herein, the composition is formulated to be administered by a route selected from the group consisting of: intravenous, intramuscular, subcutaneous, intradermal, topical, intraperitoneal, intrathecal, intrapleural, intrasynovial, intrauterine, intravaginal, intratumor, and parenteral administration.

In one embodiment, of any of the composition described herein, the composition is administered in conjunction with at least one additional cancer therapy to achieve a combination cancer therapy.

In one embodiment of any composition described herein, wherein the at least one additional cancer therapy is selected from the group consisting of radiation therapy, chemotherapy, immunotherapy and gene therapy.

In one embodiment of any composition described herein, the composition further comprises a drug that treats at least one symptom of cancer or cancer therapy. For example, for low blood count or anemia resulting from the chemo- or radiation therapy, erythropoietin can be administered to promote de novo the production of blood cell cells.

Formulation and Administration

In one embodiment, the agent that increases the expression of TNFRSF1A as described herein is delivered in a pharmaceutically acceptable carrier.

In one embodiment, the composition used in the treatment of MM comprises an agent that increases the expression of TNFRSF1A and a pharmaceutically acceptable carrier.

In one embodiment, the term “pharmaceutically acceptable” means approved by a regulatory agency of the Federal or a state government or listed in the U.S. Pharmacopeia or other generally recognized pharmacopeia for use in animals, and more particularly in humans. Specifically, it refers to those compounds, materials, compositions, and/or dosage forms which are, within the scope of sound medical judgment, suitable for use in contact with the tissues of human beings and animals without excessive toxicity, irritation, allergic response, or other problem or complication, commensurate with a reasonable benefit/risk ratio.

The term “carrier” refers to a diluent, adjuvant, excipient, or vehicle with which the therapeutic is administered. Such pharmaceutical carriers can be sterile liquids, such as water and oils, including those of petroleum, animal, vegetable or synthetic origin, such as peanut oil, soybean oil, mineral oil, sesame oil and the like. Water is a preferred carrier when the pharmaceutical composition is administered intravenously. Saline solutions and aqueous dextrose and glycerol solutions can also be employed as liquid carriers, particularly for injectable solutions. Suitable pharmaceutical excipients include starch, glucose, lactose, sucrose, gelatin, malt, rice, flour, chalk, silica gel, sodium stearate, glycerol monostearate, talc, sodium chloride, dried skim milk, glycerol, propylene, glycol, water, ethanol and the like. The composition, if desired, can also contain minor amounts of wetting or emulsifying agents, or pH buffering agents. These compositions can take the form of solutions, suspensions, emulsion, tablets, pills, capsules, powders, sustained-release formulations, and the like. The composition can be formulated as a suppository, with traditional binders and carriers such as triglycerides. Oral formulation can include standard carriers such as pharmaceutical grades of mannitol, lactose, starch, magnesium stearate, sodium saccharine, cellulose, magnesium carbonate, etc. Examples of suitable pharmaceutical carriers are described in Remington's Pharmaceutical Sciences, 18th Ed., Gennaro, ed. (Mack Publishing Co., 1990). The formulation should suit the mode of administration. Additional carrier agents, such as liposomes, can be added to the pharmaceutically acceptable carrier.

As used herein, in one embodiment, “administering” refers to the placement of an agent that increases the expression of TNFRSF1A as described herein or a composition comprising the agent into a subject by a method or route which results in at least partial localization of the agent at a desired site. The agent or composition described herein can be administered by any appropriate route which results in effective treatment in the subject, i.e. administration results in delivery to a desired location (e.g., directly to a tumor or near a tumor) in the subject where at least a portion of the composition delivered, i.e. at least some agent are active in the desired site for a period of time. The period of time that the agent is active depends on the half-life in vivo after administration to a subject, and can be as short as a few hours, e.g. twenty-four hours, to a few days, to as long as several years. Modes of administration include injection, infusion, instillation, suppository (e.g., for vaginal, cervical. rectal or urethral insertion), percutaneous implantation or ingestion. “Injection” includes, without limitation, intravenous, intramuscular, intraarterial, intraventricular, intradermal, intraperitoneal, subcutaneous, subcuticular injection and infusion.

Therapeutic compositions contain a physiologically tolerable carrier together with an agent described herein, dissolved or dispersed therein as an active ingredient. In one embodiment, the therapeutic composition is not immunogenic when administered to a mammal or human patient for therapeutic purposes. As used herein, the terms “pharmaceutically acceptable”, “physiologically tolerable” and grammatical variations thereof, as they refer to compositions, carriers, diluents and reagents, are used interchangeably and represent that the materials are capable of administration to or upon a mammal without the production of undesirable physiological effects such as nausea, dizziness, gastric upset and the like. A pharmaceutically acceptable carrier will not promote the raising of an immune response to an agent with which it is admixed, unless so desired. The preparation of a pharmacological composition that contains active ingredients dissolved or dispersed therein is well understood in the art and need not be limited based on formulation. Compositions can be prepared as injectable either as liquid solutions or suspensions, however, solid forms suitable for solution, or suspensions; in liquid prior to use can also be prepared. The preparation can also be emulsified or presented as a liposome composition. The agent described herein can also be conjugated with lipids, e.g., amphipathic lipids, for stability and delivery purposes. The conjugation bonds are reversible and are broken or dissolved when agent described herein are delivered to target destination. Alternatively, the agent described herein can be prepared as a solid or semi-solid or emulsion in suppository, e.g., as microspheres. The microspheres can be inserted as a solid into or targeted to a solid tumor. The agent described herein can be mixed with excipients which are pharmaceutically acceptable and compatible with the active ingredient and in amounts suitable for use in the therapeutic methods described herein. Specifically contemplated pharmaceutical compositions are agent described herein in a preparation for delivery as described herein above, or in references cited and incorporated herein in that section. Suitable excipients include, for example, water, saline, dextrose, glycerol, ethanol or the like and combinations thereof. In addition, if desired, the composition can contain minor amounts of auxiliary substances such as wetting or emulsifying agents, pH buffering agents and the like which enhance the effectiveness of the active ingredient. The therapeutic composition comprising the agent described herein can include pharmaceutically acceptable salts of the components therein. Pharmaceutically acceptable salts include the acid addition salts (formed with the free amino groups of the polypeptide) that are formed with inorganic acids such as, for example, hydrochloric or phosphoric acids, or such organic acids as acetic, tartaric, mandelic and the like. Salts formed with the free carboxyl groups can also be derived from inorganic bases such as, for example, sodium, potassium, ammonium, calcium or ferric hydroxides, and such organic bases as isopropylamine, trimethylamine, 2-ethylamino ethanol, histidine, procaine and the like. Physiologically tolerable carriers are well known in the art. Exemplary liquid carriers are sterile aqueous solutions that contain no materials in addition to the active ingredients and water, or contain a buffer such as sodium phosphate at physiological pH value, physiological saline or both, such as phosphate-buffered saline. Still further, aqueous carriers can contain more than one buffer salt, as well as salts such as sodium and potassium chlorides, dextrose, polyethylene glycol and other solutes. Liquid compositions can also contain liquid phases in addition to and to the exclusion of water. Exemplary of such additional liquid phases are glycerin, vegetable oils such as cottonseed oil, and water-oil emulsions. The amount of agent used in the methods described herein that will be effective in the treatment of a particular disorder or condition will depend on the nature of the disorder or condition, and can be determined by standard clinical techniques.

Routes of administration include, but are not limited to, direct injection, intradermal, intramuscular, intraperitoneal, intravenous, subcutaneous, and oral routes. The agent or compositions described herein can be administered by any convenient route, for example by infusion, intravenous injection, suppository or bolus injection, by absorption through epithelial or mucocutaneous linings (e.g., oral mucosa, rectal and intestinal mucosa, etc.) and may be administered together with other biologically active agents. Administration can be systemic or local.

The precise dose and formulation to be employed depends upon the potency of the agent, and include amounts large enough to produce the desired effect, e.g., a reduction in size and/or growth of the tumors in the subject. The dosage should not be so large as to cause unacceptable adverse side effects. Generally, the dosage will vary with the type of agent described herein, and with the age, condition, and size of the tumors in the subject are also considered. Dosage and formulation of the agent described herein will also depend on the route of administration, and the mass and number of tumors in the subject, and should be decided according to the judgment of the practitioner and each subject's circumstances. Effective doses can be extrapolated from dose-response curves derived from in vitro or animal model test systems.

The dosage can be determined by one of skill in the art and can also be adjusted by the individual physician in the event of any complication. Typically, the dosage ranges from 0.001 mg/kg body weight to 5 g/kg body weight. In some embodiments, the dosage range is from 0.001 mg/kg body weight to 1 g/kg body weight, from 0.001 mg/kg body weight to 0.5 g/kg body weight, from 0.001 mg/kg body weight to 0.1 g/kg body weight, from 0.001 mg/kg body weight to 50 mg/kg body weight, from 0.001 mg/kg body weight to 25 mg/kg body weight, from 0.001 mg/kg body weight to 10 mg/kg body weight, from 0.001 mg/kg body weight to 5 mg/kg body weight, from 0.001 mg/kg body weight to 1 mg/kg body weight, from 0.001 mg/kg body weight to 0.1 mg/kg body weight, from 0.001 mg/kg body weight to 0.005 mg/kg body weight. Alternatively, in some embodiments the dosage range is from 0.1 g/kg body weight to 5 g/kg body weight, from 0.5 g/kg body weight to 5 g/kg body weight, from 1 g/kg body weight to 5 g/kg body weight, from 1.5 g/kg body weight to 5 g/kg body weight, from 2 g/kg body weight to 5 g/kg body weight, from 2.5 g/kg body weight to 5 g/kg body weight, from 3 g/kg body weight to 5 g/kg body weight, from 3.5 g/kg body weight to 5 g/kg body weight, from 4 g/kg body weight to 5 g/kg body weight, from 4.5 g/kg body weight to 5 g/kg body weight, from 4.8 g/kg body weight to 5 g/kg body weight. In one embodiment, the dose range is from 5 g/kg body weight to 30 g/kg body weight. Alternatively, the dose range will be titrated to maintain serum levels between 5 g/mL and 30 g/mL.

Administration of the doses recited above can be repeated for a limited period of time. In some embodiments, the doses are given once a day, or multiple times a day, for example but not limited to three times a day. In one embodiment, the doses recited above are administered daily for several weeks or months. The duration of treatment depends upon the subject's clinical progress and responsiveness to therapy, e.g., shrinkage of tumor sizes. Continuous, relatively low maintenance doses are contemplated after an initial higher therapeutic dose. As exemplary, the agent described herein and a pharmaceutically acceptable carrier can be formulated for direct application by injection into the tumor in the subject.

Efficacy testing can be performed during the course of treatment using the methods described herein, e.g., ultrasound, MRI and CT to monitor the shrinkage in size of the tumors in the treated subject. A decrease in size of the tumors during and after treatment indicates that the treatment is effective in reducing tumor size. Measurements of the degree of severity of a number of symptoms associated with cancerous tumors are also noted prior to the start of a treatment and then at later specific time period after the start of the treatment. A skilled physician will be able to ascertain the tumor sizes and related symptoms by known methods in the art and those described herein.

Kits, Computer System and Computer Data Storage

In one embodiment, the disclosure herein provides a microarray chip for rapid analysis of the presence or absence of genetic mutations disclosed in Table 1 and 2, and disclosed TNFRSF1A mutations, comprising a library of nucleic acid probes for at least five genetic mutations disclosed, wherein each probe comprising a single strand nucleic acid sequence that is at least 15 nucleotides long and that is complementary to the at least 5 base pair 5′ and at least 3′ of the position of mutation disclosed. In one embodiment, the single strand nucleic acid of each probe for each genetic mutation is present in triplicates.

In one embodiment, the disclosure herein provides a kit for rapid analysis of the presence or absence of genetic mutations disclosed in Table 1 and 2, and disclosed TNFRSF1A mutations, the kit comprising a microarray chip described herein, PCR primers and reagents for isolating nucleic acid from a biological sample, and amplifying the gene regions encompassing the location of mutations disclosed in Table 1 and 2, and disclosed TNFRSF1A mutations.

In one embodiment, the library of probe is attached to a solid support as probe features in a specific arrangement wherein the location of each probe feature is known. In one embodiment, a probe feature is provided on a solid support; the probe feature being a localized and concentrated sample having multiple copies of the same probe is deposited and attached on a solid surface. For example, for a flat solid support such as on the glass-chip surface, a probe feature is a minute spot or dot printed with multiple copies of the same probe. The multiple copies can range from tens to thousands, e.g. 10-10000. All of the whole integers between 10 to 10,000 are included is a single probe feature. For a spherical surface such as a glass bead, “a probe feature” refers to a single probe-coated bead. All the beads are coated with the multiple copies of same probe that complements and interrogates a single genetic mutation. The range of numbers of probe-coated beads in “a probe feature” is between 100-1000, including all of the whole integers between 10-10000.

In one embodiment, replicates of a probe feature are made on a solid support. For a flat solid support such as a glass-chip, all replicate features of one probe feature type have one type of probe and the replicates can be arranged in a row on the glass-chip surface. Multiple rows can be made and distributed in fix and known coordinates on the glass chip. For a spherical solid support such as a glass bead, replicate features of one probe are many probe-coated beads, about 100 probe-coated beads. These beads all have probes of a single type. For each probe on a flat solid support, there are at least four replicate features, at least five, at least six, at least seven, at least eight, at least nine, and at least ten replicate features, sometimes more. In some embodiments, the solid support has between 10-50 replicate features for each unique probe. All whole integers between 10-50 are considered. For each probe on a spherical solid support, there are at least about 100 replicate features or probe-coated beads.

In one embodiment, for the practice of the methods, replicates of probe features of a first set of probe sets are provided for a genetic mutation to be interrogated. In one embodiment, for the practice of the methods, replicates of probe features of a second set of probe sets are provided for a control genetic non-mutation to be interrogated. The replicates of probe features of the first and second set of probe sets are attached on same solid support.

In accordance with some methods, two or more identical solid supports are used, each solid support having probe features. One solid support is used to hybridize with the test nucleic acid sample and the other solid support is used to hybridize with the control nucleic acid sample.

In accordance with the method where two identical solid supports are used, each solid support having all the replicates of a first and a second set of probe sets, wherein the first set of probe sets interrogates a genetic variant mutation and the second set of probe sets interrogates a genetic non-variant mutation. One solid support is used to hybridize with the test NA sample and the other solid support is used to hybridize with the control NA sample (see FIGS. 6 and 7).

In one embodiment, each probe feature is provided in at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 9, at least 10 replicates and the probe features are attached to the flat surface at positions according to a known uniform spatial distribution, i.e., a support or surface with an ordered array of binding (e.g. hybridization) sites or probes. In other embodiments, anywhere form 10-50 replicate probe features are provided. Thus, the arrangement of replicate features on the support is predetermined. Each probe replicate is located at a known predetermined position on the solid support such that the identity (i.e. the sequence) of each probe can be determined from its position on the array. Typically, the probes are uniformly distributed in a predetermined pattern.

In one embodiment, the solid support is a flat surface. For example, for a flat solid support is a glass-chip surface.

In addition to microarray or DNA-arrays in the form of DNA-chips to detect genetic mutations. It is also contemplated that DNA particle or bead suspensions are used.

In one embodiment, the solid support is a micron-size particle. In one embodiment, the beads are uniquely identifiable. Examples of particle identifiers on a particle are a bar code and a fluorescent dye. In one embodiment, the beads are bar-coded. These beads such as polymer or magnetic beads have unique spectroscopic signatures. Beads can be synthesized by dispersion polymerization of a family of styrene monomers and methacrylic acid to generate a spectroscopically encoded bead library. Raman spectroscopy is used to monitor complexing events on the barcoded beads. The genotyping assays from ILLUMINA®, Inc. uses the particles that are cylindrical beads encoded with a barcode, which are then read by a barcode scanner. Platforms such as the XMAP™ technology from LUMINEX® is have the particles that are microspheres encoded with fluorescent dyes. The particles are read by a flow cytometer.

In one embodiment, the solid supports form particle suspensions. It has been found that these particle suspensions should comply with a number of requirements in order to be used in the present methods, for example in terms of the design of the probes, the number of probes provided for each genetic variation to be detected and the distribution of probes on the support. These are described in detail herein.

In one embodiment, wherein the solid support is a micron-size particle, each probe is attached to at least 10 units of each particle species, wherein each particle species is distinguishable by a unique code from all other particle species.

In one embodiment, wherein the solid support is a micron-size particle, each probe is attached to at least 1000 units of each particle species.

In practicing the method described herein, the labeled nucleic acid (target nucleic acid) derived from the biological samples of subjects are contacted with a solid support having attached probes in a specified arrangement described herein as replicate features, allowing nucleic acid hybridization with the probes in the replicate features and the formation of target-probe complexes. Under conditions which allow hybridization to occur between target nucleic acid and the corresponding probes, specific hybridization complexes are formed between target NA and corresponding probes. Since the nucleic acids are labeled, the target-probe complexes formed can therefore be detected.

Typically, the hybridization conditions allow specific hybridization between probes and corresponding target nucleic acid to form specific probe/target hybridization complexes while minimizing hybridization between probes carrying one or more mismatches to the DNA. Such conditions may be determined empirically, for example by varying the time and/or temperature of hybridization and/or the number and stringency of the array washing steps that are performed following hybridization and are designed to eliminate all probe-DNA interactions that are non-specific. For example, the melting temperature of the probe/target complexes may occur at 75-85° C. In some embodiments, hybridizations can be for one hour, although higher and lower temperatures and longer or shorter hybridizations may also suffice. A skilled artisan can optimize these conditions using routine methods.

The hybridization can be carried out using conventional methods and devices. In one instance, hybridization is carried out using an automated hybridization station. For hybridization to occur, the mutations are placed in contact with the probes under conditions which allow hybridization to take place. Using stable hybridization conditions allows the length and sequence of the probes to be optimized in order to maximize the discrimination between genetic variations A and B, e.g. between wild type and mutant sequences, as described herein.

In general a chip DNA array has from 300 to 40000 probe features, for example, from 400 to 30000 or 400 to 20000. The chip can have from 1000 to 20000 probes, such as 1000 to 15000 or 1000 to 10000, or 1000 to 5000. A suitable chip may have from 2000 to 20000, 2000 to 10000 or 2000 to 5000 probe features. For example, a chip may have 1000, 2000, 3000, 4000, 5000, 6000, 7000, 8000, 9000, 10000, 12000, 14000, 16000, 18000 or 20000 probes. Smaller chips 400 to 1000 probes, such as 400, 500, 600, 700, 800, 900 or 950 probes are also envisaged. The number of probes in a particle suspension will vary depending on the number of individually identifiable particles.

In general the chip DNA array of the invention comprises a support or surface with an ordered array of binding (e.g. hybridization) sites or probe features. Thus the arrangement of probes on the support is predetermined. Each probe (i.e each replicate feature) is located at a known predetermined position on the solid support such that the identity (i.e. the sequence) of each probe can be determined from its position in the array. Typically the probes are uniformly distributed in a predetermined pattern.

Preferably, the probes deposited on the support, although they maintain a predetermined arrangement, are not grouped by genetic variation but have a random distribution. Typically they are also not grouped within the same genetic variation. If desired, this random distribution can be always the same. Therefore, typically the probes are deposited on the solid support (in an array) following a predetermined pattern so that they are uniformly distributed, for example, between the two areas that may constitute a DNA-chip, but not grouped according to the genetic variation to be characterized. Distributing probe replicates across the array in this way helps to reduce or eliminate any distortion of signal and data interpretation, e.g. arising from a non-uniform distribution of background noise across the array.

In some embodiments, probe features are arranged on the support in subarrays. Microarrays are in general prepared by selecting probes which comprise a given polynucleotide sequence, and then immobilizing such probes to a solid support or surface. Probes may be designed, tested and selected as described herein. In general, the probes can comprise DNA sequences. In some embodiments the probes may comprise RNA sequences, or copolymer sequences of DNA and RNA. The polynucleotide sequences of the probes may also comprise DNA and/or RNA analogues, or combinations thereof. For example, the polynucleotide sequences of the probes may be full or partial fragments of genomic DNA. The polynucleotide sequences of the probes may also be synthesized nucleotide sequences, such as synthetic oligonucleotide sequences. The probe sequences can be synthesized either enzymatically in vivo, enzymatically in vitro (e.g., by PCR), or non-enzymatically in vitro.

Microarrays or chips can be made in a number of ways. However produced, microarrays typically share certain characteristics. The arrays are reproducible, allowing multiple copies of a given array to be produced and easily compared with each other. Preferably, microarrays are made from materials that are stable under binding (e.g., nucleic acid hybridization) conditions. The microarrays are preferably small, e.g., between 0.25 to 25 or 0.5 to 20 cm2, such 0.5 to 20 cm2 or 0.5 to 15 cm2, for example, 1 to 15 cm2 or 1 to 10 cm2, such as 2, 4, 6 or 9 cm2.

Replicate probe features can be attached to the solid support using conventional techniques for immobilization of oligonucleotides on the surface of the supports. The techniques used depend, amongst other factors, on the nature of the support used—porous (membranes, micro-particles, etc.) or non-porous (glass, plastic, silicone, etc.) In general, the probes can be immobilized on the support either by using non-covalent immobilization techniques or by using immobilization techniques based on the covalent binding of the probes to the support by chemical processes.

Preparation of non-porous supports (e.g., glass, silicone, plastic) requires, in general, either pre-treatment with reactive groups (e.g., amino, aldehyde) or covering the surface of the support with a member of a specific binding pair (e.g. avidin, streptavidin). Likewise, in general, it is advisable to pre-activate the probes to be immobilized by means of corresponding groups such as thiol, amino or biotin, in order to achieve a specific immobilization of the probes on the support.

The immobilization of the probes on the support can be carried out by conventional methods, for example, by means of techniques based on the synthesis in situ of probes on the support (e.g., photolithography, direct chemical synthesis, etc.) or by techniques based on, for example, robotic arms which deposit the corresponding pre-synthesized probe (e.g. printing without contact, printing by contact) (See U.S. Pat. No. 7,281,419 for example).

In one embodiment, the support is a glass slide and in this case, the probes, in the number of established replicates (for example, 6, 8 or 10) are printed on pre-treated glass slides, for example coated with aminosilanes, using equipment for automated production of DNA-chips by deposition of the oligonucleotides on the glass slides (“micro-arrayer”). Deposition is carried out under appropriate conditions, for example, by means of crosslinking with ultraviolet radiation and heating (80° C.), maintaining the humidity and controlling the temperature during the process of deposition, typically at a relative humidity of between 40-50% and typically at a temperature of 20° C.

The replicate probe features are distributed uniformly amongst the areas or sectors (sub-arrays), which typically constitute a DNA-chip. The number of replicas and their uniform distribution across the DNA-chip minimizes the variability arising from the printing process that can affect experimental results.

To control the quality of the manufacturing process of the DNA-chip, in terms of hybridization signal, background noise, specificity, sensitivity and reproducibility of each replica as well as differences caused by variations in the morphology of the spotted probe features after printing, a commercially synthesize NA can be used.

In contrast to chip DNA array technology, in which the probes are attached to the solid support at known locations, particle suspension technology allows for the detection of probes in a single vessel, with individual probes attached to a particle with a distinguishable characteristic. In some embodiments the particles are encoded with one or more optically distinguishable dyes, a detectable label, or other identifying characteristic such as a bar code. Other labeling methods include, but are not limited to a combination of fluorescent and non-fluorescent dyes, or avidin coating for binding of biotinylated ligands. Such methods of encoding particles are known in the art.

Once hybridization has taken place, the intensity of detectable label at each probe position (including control probes) can be determined. The intensity of the signal (the raw intensity value) is a measure of hybridization at each replicate feature.

The intensity of detectable label at each probe position (each probe feature replica) can be determined using any suitable means. The means chosen will depend upon the nature of the label. In general an appropriate device, for example, a scanner, collects the image of the hybridized and developed DNA-chip. An image is captured and quantified.

In one instance, e.g. where fluorescent labeling is used, after hybridization, the hybridized and developed DNA-chip is placed in a scanner in order to quantify the intensity of labeling at the points where hybridization has taken place. Although practically any scanner can be used, in one embodiment a fluorescence confocal scanner is used. In this case, the DNA-chip is placed in the said apparatus and the signal emitted by the fluorpohore due to excitation by a laser is scanned in order to quantify the signal intensity at the points where hybridization has taken place. Non-limiting examples of scanners which can be used according to the present invention include scanners marketed by the following companies: Axon, Agilent, Perkin Elmer, etc.

In one aspect of the invention, the signal from the particles is detected by the use of a flow cytometer. In other embodiments, detection of fluorescent labels may also be carried out using a microscope or camera that will read the image on the particles. Flow cytometric software for detection and analysis of the signal is available for example from Luminex, Inc. (Austin, Tex.).

In one embodiment, wherein the measuring intensity of the detectable label for each probe is performed using scanning.

In one embodiment, wherein the measuring intensity of the detectable label for each probe is performed using flow measuring systems.

Typically, in determining the intensity of detectable label at each probe position (i.e for each probe feature replica), account is taken of background noise, which is eliminated. Background noise arises because of non-specific binding to the probe array and can be determined by means of controls included in the array. Once the intensity of the background signal has been determined, this can be subtracted from the raw intensity value for each probe replica in order to obtain a clean intensity value. Typically the local background, based on the signal intensity detected in the vicinity of each individual feature is subtracted from the raw signal intensity value. This background is determined from the signal intensity in a predetermined area surrounding each feature (e.g. an area of X, Y or Z μm² centered on the position of the probe). The background signal is typically determined from the local signal of “blank” controls (solvent only). In many instances the device, e.g. scanner, which is used to determine signal intensities will provide means for determining background signal.

Thus, for example, where the label is a fluorescent label, absolute fluorescence values (raw intensity values) can be gathered for each probe replica and the background noise associated with each probe replica can also be assessed in order to produce “clean” values for signal intensity at each replicate feature position.

Once the test DNA has been hybridized to the chip and the intensity of detectable label has been determined at the probe feature replica positions on the chip (the raw intensity values), it is necessary to provide a method (model) which can relate the intensity data from the chip to the genotype of the individual.

The algorithm and computer software can be used for analysis of the genetic mutations with sufficient sensitivity and reproducibility as to allow use in a clinical setting.

Embodiments disclosed herein also provide for systems (and computer readable media for causing computer systems) to perform a method for surveillance, diagnosing, prognosing and subtyping MM in a subject.

In one embodiment, provided herein is a system comprising: a measuring module measuring a profile of genetic mutations comprising a detectable signal from an assay indicating the presence of at least one genetic mutation from a biological sample obtained from a subject; a storage module configured to store data output from the measuring module; a comparison module adapted to compare the data stored on the storage module with reference and/or control data, and to provide a retrieved content, and an output module for displaying the retrieved content for the user, wherein the retrieved content the presence of detectable at least one genetic mutation indicates that the subject has MM or has a relapse of MM.

In one embodiment, the at least one genetic mutation is one disclosed in Table 1.

In one embodiment, the at least one genetic mutation is one disclosed in Table 2.

In one embodiment, the at least one genetic mutation is one disclosed in FIG. 1 of TNFRSF1A.

In another embodiment, the at least one genetic mutation is one that is disclosed in Table 2. In another embodiment, the at least one genetic mutation is one that is disclosed herein for the human TNFRSF1A gene. In another embodiment, the at least one genetic mutation is one that is disclosed herein in FIG. 1 for the human TNFRSF1A gene. In another embodiment, the at least one genetic mutation is one that is disclosed herein for the human TNFRSF1A gene. In another embodiment, the at least one genetic mutation is not one that is disclosed in Table 2.

In one embodiment, the measuring module is capable of measuring or handling more than one genetic mutation, e.g., two, three, four, five, six, seven, eight, nine, ten or even more. In one embodiment, the measuring module measures the profile of genetic mutations from a microarray chip described herein. In one embodiment, the assay indicating the presence of at least one genetic mutation from a biological sample obtained from a subject comprises a microarray chip described herein. In one embodiment, the detectable signal from the assay is a detectable signal from a hybridized nucleic acid to the nucleic acid probe sequence on the array chip, wherein the hybridized nucleic acid is detectably labeled and wherein a detectable signal indicates the presence of the mutation set forth for that complementary nucleic acid probe sequence.

In one embodiment, the reference and/or control data is the genetic mutation profile of the same subject at an earlier time point, e.g., prior to start of treatment. In one embodiment, the reference and/or control data is the entire collection of mutations disclosed in Tables 1 and 2 and the human TNFRSF1A gene. In another embodiment, the reference and/or control data is the collection of mutations characteristic for the subtypes of MM according to the method described herein.

In one embodiment, provided herein is a system to facilitate the prognosis evaluation of MM in a subject, comprising: a determination (measuring) module configured to receive and output the presence of at least one genetic mutation from a biological sample obtained from a subject; a storage module configured to store output information from the determination module; a comparison module adapted to compare the data stored on the storage module with reference and/or control data, and to provide a comparison content, and an output module for displaying the comparison content for the user. If there is at least one detected genetic mutation disclosed herein, then the subject likely has MM if the subject have not been previously diagnosed with MM or the subject has a relapse if the subject has been in remission and has minimal or no detectable mutations at start of remission. If there is an increase in the number of mutations, then the MM in the subject is progressing, and the current treatment is not effective. If there is a decrease in the number of mutations, then the MM in the subject is regressing, and the current treatment is effective.

In one embodiment, the reference and/or control data is the genetic mutation profile of the same subject at an earlier time point, e.g., prior to start of treatment. In one embodiment, the reference and/or control data is the entire collection of mutations disclosed in Tables 1 and 2 and the human TNFRSF1A gene. In another embodiment, the reference and/or control data is the collection of mutations characteristic for the subtypes of MM according to the method described herein. In some embodiments, the control data comprises previous data from the same subject wherein the previous data had indicated the presence of at least one genetic mutation, the specific gene having the mutation and the number of mutations.

In one embodiment, provided herein is a computer readable storage medium comprising: a storing data module containing data from a biological sample obtained from a subject that a profile of genetic mutations comprising a detectable signal from an assay indicating the presence of at least one genetic mutation; a comparison module that compares the data stored on the storing data module with a reference data and/or control data, and to provide a comparison content, and an output module displaying the comparison content for the user. If there is at least one detected genetic mutation disclosed herein, then the subject likely has MM if the subject have not been previously diagnosed with MM or the subject has a relapse if the subject has been in remission and has minimal or no detectable mutations at start of remission. If there is an increase in the number of mutations, then the MM in the subject is progressing, and the current treatment is not effective. If there is a decrease in the number of mutations, then the MM in the subject is regressing, and the current treatment is effective.

Embodiments of disclosed herein can be described through functional modules, which are defined by computer executable instructions recorded on computer readable media and which cause a computer to perform method steps when executed. The modules are segregated by function for the sake of clarity. However, it should be understood that the modules/systems need not correspond to discreet blocks of code and the described functions can be carried out by the execution of various code portions stored on various media and executed at various times. Furthermore, it should be appreciated that the modules may perform other functions, thus the modules are not limited to having any particular functions or set of functions.

The computer readable storage media #30 can be any available tangible media that can be accessed by a computer. Computer readable storage media includes volatile and nonvolatile, removable and non-removable tangible media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data. Computer readable storage media includes, but is not limited to, RAM (random access memory), ROM (read only memory), EPROM (eraseable programmable read only memory), EEPROM (electrically eraseable programmable read only memory), flash memory or other memory technology, CD-ROM (compact disc read only memory), DVDs (digital versatile disks) or other optical storage media, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage media, other types of volatile and non-volatile memory, and any other tangible medium which can be used to store the desired information and which can accessed by a computer including and any suitable combination of the foregoing.

Computer-readable data embodied on one or more computer-readable media may define instructions, for example, as part of one or more programs that, as a result of being executed by a computer, instruct the computer to perform one or more of the functions described herein, and/or various embodiments, variations and combinations thereof. Such instructions may be written in any of a plurality of programming languages, for example, Java, J#, Visual Basic, C, C#, C++, Fortran, Pascal, Eiffel, Basic, COBOL assembly language, and the like, or any of a variety of combinations thereof. The computer-readable media on which such instructions are embodied may reside on one or more of the components of either of a system, or a computer readable storage medium described herein, may be distributed across one or more of such components.

The computer-readable media may be transportable such that the instructions stored thereon can be loaded onto any computer resource to implement the aspects of the technology discussed herein. In addition, it should be appreciated that the instructions stored on the computer-readable medium, described above, are not limited to instructions embodied as part of an application program running on a host computer. Rather, the instructions may be embodied as any type of computer code (e.g., software or microcode) that can be employed to program a computer to implement aspects of the present technology. The computer executable instructions may be written in a suitable computer language or combination of several languages. Basic computational biology methods are known to those of ordinary skill in the art and are described in, for example, Setubal and Meidanis et al., Introduction to Computational Biology Methods (PWS Publishing Company, Boston, 1997); Salzberg, Searles, Kasif, (Ed.), Computational Methods in Molecular Biology, (Elsevier, Amsterdam, 1998); Rashidi and Buehler, Bioinformatics Basics: Application in Biological Science and Medicine (CRC Press, London, 2000) and Ouelette and Bzevanis Bioinformatics: A Practical Guide for Analysis of Gene and Proteins (Wiley & Sons, Inc., 2nd ed., 2001).

The functional modules of certain embodiments disclosed herein include at minimum a measuring module #40, a storage module #30, a comparison module #80, and an output module #110. The functional modules can be executed on one, or multiple, computers, or by using one, or multiple, computer networks. The measuring module has computer executable instructions to provide e.g., presence or absence of genetic mutation information in computer readable form. For example, the signal from detectably labeled nucleic acids that have hybridized to attached probe nucleic acid sequences on a microarray chip.

The measuring module #40, can comprise any system for detecting a signal representing the presence of a genetic mutation. Such systems can include DNA microarrays, RNA expression arrays, any ELISA detection system and/or any Western blotting detection system.

The information determined in the determination system can be read by the storage module #30. As used herein the “storage module” is intended to include any suitable computing or processing apparatus or other device configured or adapted for storing data or information. Examples of electronic apparatus suitable for use with the present technology include stand-alone computing apparatus, data telecommunications networks, including local area networks (LAN), wide area networks (WAN), Internet, Intranet, and Extranet, and local and distributed computer processing systems. Storage modules also include, but are not limited to: magnetic storage media, such as floppy discs, hard disc storage media, magnetic tape, optical storage media such as CD-ROM, DVD, electronic storage media such as RAM, ROM, EPROM, EEPROM and the like, general hard disks and hybrids of these categories such as magnetic/optical storage media. The storage module is adapted or configured for having recorded thereon expression level or protein level information. Such information may be provided in digital form that can be transmitted and read electronically, e.g., via the Internet, on diskette, via USB (universal serial bus) or via any other suitable mode of communication.

As used herein, “stored” refers to a process for encoding information on the storage module. Those skilled in the art can readily adopt any of the presently known methods for recording information on known media to generate manufactures comprising expression level information.

In one embodiment the reference data stored in the storage module to be read by the comparison module is e.g., genetic mutation profiles obtained from a population of non-MM subjects, a database of genetic mutation profiles of MM subjects or a genetic mutation profile obtained from the same subject at a prior time point using the measuring module #40.

The “comparison module” #80 can use a variety of available software programs and formats for the comparison operative to compare the genetic mutation profiles or the presence or absence of mutations determined in the measuring module to reference samples and/or stored reference data. In one embodiment, the comparison module is configured to use pattern recognition techniques to compare information from one or more entries to one or more reference data patterns. The comparison module may be configured using existing commercially-available or freely-available software for comparing patterns, and may be optimized for particular data comparisons that are conducted. The comparison module provides computer readable information related to normalized genetic mutation profiles, presence/absence of MM in an individual, efficacy of treatment in an individual, and/or method for treating an individual.

The comparison module, or any other module of systems described, may include an operating system (e.g., UNIX) on which runs a relational database management system, a World Wide Web application, and a World Wide Web server. World Wide Web application includes the executable code necessary for generation of database language statements (e.g., Structured Query Language (SQL) statements). Generally, the executables will include embedded SQL statements. In addition, the World Wide Web application may include a configuration file which contains pointers and addresses to the various software entities that comprise the server as well as the various external and internal databases which must be accessed to service user requests. The configuration file also directs requests for server resources to the appropriate hardware—as may be necessary should the server be distributed over two or more separate computers. In one embodiment, the World Wide Web server supports a TCP/IP protocol. Local networks such as this are sometimes referred to as “Intranets.” An advantage of such Intranets is that they allow easy communication with public domain databases residing on the World Wide Web (e.g., the GenBank™ or Swiss Pro World Wide Web site). Thus, in a particular preferred embodiment of the present technology, users can directly access data (via Hypertext links for example) residing on Internet databases using a HTML interface provided by Web browsers and Web servers.

The comparison module provides a computer readable comparison result that can be processed in computer readable form by predefined criteria, or criteria defined by a user, to provide a content-based in part on the comparison result that may be stored and output as requested by a user using an output module #110.

The content based on the comparison result, may be a genetic mutation profile compared to a reference showing the presence/absence of MM in a subject or the subtype of MM in the subject.

In one embodiment of the system, the content based on the comparison result is displayed on a computer monitor #120. In one embodiment of the system, the content based on the comparison result is displayed through printable media #130, #140. The display module can be any suitable device configured to receive from a computer and display computer readable information to a user. Non-limiting examples include, for example, general-purpose computers such as those based on Intel PENTIUM-type processor, Motorola PowerPC, Sun UltraSPARC, Hewlett-Packard PA-RISC processors, any of a variety of processors available from Advanced Micro Devices (AMD) of Sunnyvale, Calif., or any other type of processor, visual display devices such as flat panel displays, cathode ray tubes and the like, as well as computer printers of various types.

In one embodiment, a World Wide Web browser is used for providing a user interface for display of the content based on the comparison result. It should be understood that other modules of the technology can be adapted to have a web browser interface. Through the Web browser, a user may construct requests for retrieving data from the comparison module. Thus, the user will typically point and click to user interface elements such as buttons, pull down menus, scroll bars and the like conventionally employed in graphical user interfaces.

Therefore, provided herein are systems (and computer readable media for causing computer systems) to perform methods for surveillance of MM (by detecting the presence of specified genetic mutation); for diagnosing MM (by detecting the presence of specified genetic mutation); for subtyping MM (by the specific profile of genetic mutations) or for assessing treatment prognosis of MM in an individual (by the changes of specific genetic mutations).

Systems and computer readable media described herein are merely illustrative embodiments described herein for surveillance, diagnosing, prognosing and subtyping MM in a subject, and are not intended to limit the scope of the technology. Variations of the systems and computer readable media described herein are possible and are intended to fall within the scope of the technology.

The modules of the machine, or those used in the computer readable medium, may assume numerous configurations. For example, function may be provided on a single machine or distributed over multiple machines.

The present technology can be defined in any of the following numbered paragraphs:

[1] A method for surveillance for malignant mesothelioma (MM) in a subject comprising: detecting the presence of at least one genetic mutation listed in Tables 1 and 2 and in a TNFRSF1A gene in a biological sample obtained from the subject; and subjecting the subject to at least one addition diagnostic test selected from the group consisting of chest X-ray, MRI, CT scan, PET scan, thoracentesis, mediastinoscopy, echocardiogram and thoracoscopy when at least one mutation is detected. [2] The method of claim 1, wherein the subject is not been differentially diagnosed with MM. [3] The method of claim 1 or 2, wherein the subject is male or female. [4] The method of claim 1, 2 or 3, wherein the subject is between the ages of 35-95. [5] The method of claim 4, wherein the subject is 50 years and older. [6] The method of any one of claims 1-5, wherein the subject has prior exposure to asbestos. [7] The method of any one of claims 1-5, wherein the subject lives or has lived with a person who works with asbestos or had prior exposure to asbestos. [8] The method of any one of claims 1-5, wherein the subject has no known prior exposure to asbestos. [9] The method of any one of claims 1-8, wherein the method is performed on a schedule selected from the group consisting of monthly, once every two months, once every three months, once every two months, once every five months, and once every six months and once yearly. [10] The method of any one of claims 1-9, wherein the subject is asymptomatic for a common respiratory ailment. [11] The method of any one of claims 1-9, wherein the subject has at least one symptom selected from the group anemia, blood clotting disorder, bowel obstruction, chest pain, persistent dry or raspy cough, coughing up blood (hemoptysis), shortness of breath (dyspnea), pain in the lower back or rib area, painful breathing, development of lumps under the skin on the chest, difficulty with swallowing (dysphagia), night sweats or fever, nausea, unexplained weight loss, fatigue, abdomen, pericardium, peritoneal and/or pleural effusion. [12] The method of any one of claims 1-11, wherein the detecting comprising providing the biological sample obtained from the subject; and analyzing for the presence of at least one mutation disclosed in Tables 1 and 2 and in a TNFRSF1A gene. [13] The method of claim 12, wherein the detecting further comprising extracting the nucleic acid from the biological sample prior to analysis for genetic mutations. [14] The method of any one of claims 1-13, further comprising selecting a subject who is at risk of developing MM. [15] The method of any one of claims 1-14, further comprising detecting for the presences of all the mutations disclosed in Tables 1 and 2 to generate a profile of gene mutations. [16] The method of any one of claims 1-15, wherein at least one mutation is detected, the method further comprising assigning a subtype of MM to the subject based the profile of gene mutations. [17] The method of any one of claims 1-16, further comprising inputting the profile of gene mutations into a computer system equipped with a computer software for analyzing the profile of gene mutations and assigning a subtype of MM to the profile of gene mutations. [18] A method of classifying subtypes of malignant mesothelioma (MM) based on profiles of genetic mutations in a population of subjects having MM comprising: a) providing a genetic mutation profile database comprising profiles of genetic mutation of the genes of Tables 1 and 2 and in a TNFRSF1A gene at the specific location indicated in Tables 1 and 2 and in a TNFRSF1A gene from a population of subjects having MM and prior to any treatment; b) applying the genetic mutation database to a clustering algorithm which analyzes and identifies at least two separate and distinct clusters within the database, wherein each cluster comprising a collection of genetic mutations of Tables 1 and 2 and in a TNFRSF1A gene; c) sorting the population of subjects having MPM into the at least two separate and distinct clusters identified by the clustering algorithm; d) monitoring the treatment regimen and prognosis of the subjects separated into the clusters of step c; e) correlating the treatment regimen and prognosis of the subjects with the subject's designated cluster; f) determining which treatment regimen for each cluster result in at least 2 fold increase in survival over the median survival time; and g) associating the treatment regimen of step f with the respective cluster to form a subtype. [19] The method of claim 18, wherein the profile of genetic mutation is obtained by providing a biological sample from each subject of the population; and analyzing for the presence of all the genetic mutations disclosed in Tables 1 and 2 and in a TNFRSF1A gene. [20] The method of claim 19, wherein the method further comprising extracting the nucleic acid from the biological sample prior to the analysis of genetic mutation. [21] The method of claim 18, 19 or 20, wherein step b and step c are performed using a computer system equipped with a clustering algorithm for analyzing the profiles of gene mutations and assigning a subtype of MM to the profile of gene mutations. [22] A method of subtyping malignant mesothelioma (MM) in a subject comprising: a) detecting for the presences of all the mutations disclosed in Tables 1 and 2 and in a TNFRSF1A gene to generate a profile of gene mutations; b) comparing the profile of gene mutations with a collection of genetic mutations associated with each subtypes identified in the method of claim 18-21; and c) assigning a subtype of MPM when the profile of gene mutations of the subject matches the collection by a 70 percentile. [23] The method of claim 22, wherein the profile of genetic mutation is produced by providing a biological sample from each subject of the population; and analyzing for the presence of all the genetic mutations disclosed in Tables 1 and 2 and in a TNFRSF1A gene disclose FIG. 1. [24] The method of claim 23, wherein the method further comprising extracting the deoxyribonucleic acid from the biological sample prior to the analysis of genetic mutation. [25] The method of claim 22, 23 or 24, wherein step b and step c are performed using a computer system equipped with a clustering algorithm for analyzing the profiles of gene mutations and assigning a subtype of MM to the profile of gene mutations. [26] A method for monitoring the progression or regression of a subject having malignant mesothelioma (MM), the method comprising: a) monitoring the presence or absence of at least one genetic mutation listed in Tables 1 and 2, and disclosed TNFRSF1A mutations or listed in a collection of gene mutations characteristic of a subtype of MPM in a biological sample from the subject prior to a treatment or at a first time during the course of a treatment; b) monitoring the presence or absence of the at least one genetic mutation listed in Tables 1 and 2, and disclosed TNFRSF1A mutations or listed in a collection of gene mutations characteristic of a subtype of MPM in another biological sample from the subject at a second time during the course of a treatment, wherein the first and second time are in chronological order, and wherein the same genetic mutation is monitored; and c) comparing the first measurement and the second measurement, wherein the comparative measurements determine the course of MM. [27] The method of claim 26, wherein there is no disappearance of the at least one genetic mutation during the course of treatment when the at least one genetic mutation is present prior to start of treatment or at the first time indicating progression of MM. [28] The method of claim 26, wherein there is appearance of the at least one genetic mutation during the course of treatment when the at least one genetic mutation is absent prior to start of treatment or at the first time indicating progression of MM. [29] The method of claim 26, wherein there is disappearance of the at least one genetic mutation during the course of treatment, when the at least one genetic mutation is present prior to start of treatment or at the first time indicating regression of MM. [30] The method of claim 27 or 28, further comprising terminating current treatment. [31] The method of claim 30, further comprising commencing another treatment when current treatment is terminated. [32] The method of any one of claims 26-31, wherein the collection of gene mutations characteristic of a subtype of MM is determined by the method of claims 18-21. [33] The method of any one of claims 26-32, wherein the subject is identified as having a subtype of MM by the method of claim 22-25. [34] A method for treating malignant mesothelioma (MM) in a subject comprising: a) categorizing the MM to a subtype according to the method of claim 22-25; and b) administering an effective treatment regime to the subject based on the subtype. [35] A composition comprising an agent that increases the expression of a tumor necrosis factor receptor superfamily member 1A (TNFRSF1A) for use in the treatment of malignant mesothelioma (MM). [36] Use of an agent that increases the expression of a tumor necrosis factor receptor superfamily member 1A (TNFRSF1A) for the treatment of malignant mesothelioma (MM). [37] The composition of claim 35, wherein the agent is thalidomide or lenalidomide (levlimid). [38] The composition of claim 35, wherein the agent is a nucleic acid sequence comprising the human sequence TNFRSF1A mRNA sequence NM_(—)001065.2. [39] The composition of claim 35, wherein the agent is a nucleic acid sequence comprising SEQ. ID. NO:1. [40] The composition of claim 35, wherein the agent is a vector or DNA construct comprising a nucleic acid sequence SEQ. ID. NO:1. [41] The use of any one of claims 35, 37-40, wherein the MM is malignant pleural mesothelioma (MPM). [42] The use of claim 36, wherein the agent is thalidomide or lenalidomide (levlimid). [43] The use of claim 36, wherein the agent is a nucleic acid sequence comprising the human sequence TNFRSF1A mRNA sequence NM_(—)001065.2. [44] The use of claim 36, wherein the agent is a nucleic acid sequence comprising SEQ. ID. NO:1. [45] The use of claim 36, wherein the agent is a vector or DNA construct comprising a nucleic acid sequence SEQ. ID. NO:1. [46] The use of any one of claims 36, 42-45, wherein the MM is malignant pleural mesothelioma (MPM). [47] A method for treating MM in a subject comprising administering to a subject in need thereof a therapeutically effective amount of an agent that increases the expression of a tumor necrosis factor receptor superfamily member 1A (TNFRSF1A). [48] A method for treating MM in a subject comprising administering to a subject in need thereof a composition of any one of claims 35-40. [49] The method of claim 34, 47 or 48, further comprising selecting a subject who is in need of treatment. [50] The method of claim 49, wherein the subject has been diagnosed with MM. [51] The method of claim 49, wherein the diagnosis of MM is according to any one of claims 1-17. [52] The method of any one of claims 34, 47-51, wherein the subject has been subtyped according to any one of claims 22-25. [53] The method of any one of claims 1-34, 47-52, wherein the MM is malignant pleural mesothelioma (MPM).

TABLE 1 Nuc_(—) Chromo- Offset/ Variant_(—) ID Gene_Name Status some location S_base CG10 OR2G3 Mutation 1 247769183 C > T CG10 B3GALT5 Mutation 21 41032932 C > T CG10 APOBEC2 Mutation 6 41029405 G > A CG10 SVEP1 Mutation 9 113198689 G > A CG10 PRPF39 Mutation 14 45571854 G > C CG10 TNFRSF1A Mutation 12 6439791 G > A CG10 CHD8 Mutation 14 21860041 C > G CG10 SLFN5 Mutation 17 33585956 A > G CG10 PCDH18 Mutation 4 138451172 C > T CG10 HNRNPA0 Mutation 5 137088882 C > T CG10 SCRN2 Mutation 17 45915248 G > A CG10 MYO1B Mutation 2 192160934 A > G CG10 OR2C3 Mutation 1 247694861 G > A CG10 DAGLB Mutation 7 6450010 T > C CG10 IL4R Mutation 16 27353546 C > T CG10 CDAN1 Mutation 15 43020421 G > A CG10 MYH9 Mutation 22 36682841 C > A CG10 RNF43 Mutation 17 56437557 C > T CG10 CRY2 Mutation 11 45893729 C > T CG12 TNRC6C Mutation 17 76087600 G > T CG12 TIRAP Mutation 11 126162525 C > T CG12 OTX2 Mutation 14 57268490 T > C CG12 GANAB Mutation 11 62402341 T > C CG12 MARK2 Mutation 11 63668273 A > C CG12 CAPN1 Mutation 11 64955495 G > A CG12 DDX25 Mutation 11 125788560 T > C CG12 PEX5L Mutation 3 179537665 T > C CG12 IL19 Mutation 1 207010065 G > A CG14 TP53 Mutation 17 7578257 C > A CG14 USP9X Mutation X 41075851 C > G CG14 PTPRT Mutation 20 40730859 G > A CG14 MYH6 Mutation 14 23876383 C > T CG14 KIAA1024 Mutation 15 79750129 C > T CG14 KIAA1958 Mutation 9 115421933 A > T CG16 NLGN1 Mutation 3 173998909 C > T CG16 ZNF597 Mutation 16 3487145 T > A CG16 ZNF552 Mutation 19 58319916 G > A CG18 TP53 Mutation 17 7578190 T > G CG18 AHRR Mutation 5 428111 G > A CG18 ITGA1 Mutation 5 52177726 G > A CG20 PIK3C2A Mutation 11 17156495 G > A CG20 FBN3 Mutation 19 8167658 A > G CG20 PRMT7 Mutation 16 68386306 G > T CG20 T Mutation 6 166580328 G > C CG20 NLRP5 Mutation 19 56549488 A > G CG20 FRMPD4 Mutation X 12734451 C > G CG20 DDX3X Mutation X 41204545 A > G CG20 COL6A6 Mutation 3 130368350 A > G CG20 GATAD2A Mutation 19 19616227 T > C CG20 KIF24 Mutation 9 34271880 T > A CG20 CENPE Mutation 4 104080019 G > A CG20 CFHR5 Mutation 1 196973914 A > T CG3 KIAA1239 Mutation 4 37445413 C > A CG3 NMUR2 Mutation 5 151784323 C > T CG3 GGNBP2 Mutation 17 34945641 G > A CG3 NFRKB Mutation 11 129751730 C > A CG3 DYSF Mutation 2 71788995 A > T CG3 MYH10 Mutation 17 8526324 G > A CG3 PTRH2 Mutation 17 57775306 C > A CG3 GPC5 Mutation 13 92346020 T > A CG4 MAP2 Mutation 2 210559268 G > A CG4 CACNA1I Mutation 22 40058186 A > G CG4 TNNT3 Mutation 11 1953725 G > A CG4 TNPO1 Mutation 5 72183040 A > C CG4 XIRP2 Mutation 2 168103556 C > A CG4 EIF3B Mutation 7 2394746 T > C CG4 KLHL23 Mutation 2 170597912 G > T CG4 ATG2B Mutation 14 96757178 C > T CG4 RHOA Mutation 3 49412929 C > T CG4 KIAA0317 Mutation 14 75138156 A > C CG4 NOS1 Mutation 12 117703189 C > T CG5 DNHD1 Mutation 11 6591295 T > G CG5 HMCN1 Mutation 1 185958651 A > C CG5 INTS3 Mutation 1 153745477 G > C CG5 HMGCS1 Mutation 5 43292673 T > C CG5 RNF169 Mutation 11 74547153 A > T CG5 KBTBD2 Mutation 7 32909033 G > A CG9 ZNF407 Mutation 18 72775924 G > A CG9 DSG1 Mutation 18 28935301 A > T CG9 SUV39H1 Mutation X 48564744 A > G CG9 ATP6V1H Mutation 8 54730047 C > G CG9 CPD Mutation 17 28776758 G > A CG9 NHSL1 Mutation 6 138754440 C > T CG9 EPS8L2 Mutation 11 709586 G > C

TABLE 2 Cancer-associated genetic lesions in MPM patients IMP Entrez Patent AA BLOSUM Gene No. Gene Symbol Accession # Chromosome Variant Change Score Name Somatic Mutation 1 ACTRA1A NM_005736.2 10q24.32 a413g K→R 2 ARP1 actin-related protein 1 homolog 1 MSRA5 NM_015419.1 Xp22.33 c7862a A→V 0 matrix-remodelling associated 1 PDZK1IP1 NM_005764.3 1p33 c403t T→I −1 PDZK1 interacting protein 1 1 PSMD13 NM_175932.1 11p15.5 c1254a L→M 2 proteasome (26S subunit 13 1 UQCRC1 NM_003365.2 3p21.3 g851a R→H 0 ubiquinol-cytochrome c reductase core protein 1 3 COL5A2 NM_000393.3 2q14-q32 c2773t P→L −3 collagen, type V, alpha 2 3 XRCC6 NM_001469.3 22q13.2-q13.31 g956a V→M 1 X-ray repair (Ku autoantigen, 70 kDa) LOH due to deletion 1 LRP10 NM_014045.3 11q11.2 g1998a R→Q 1 LDL receptor-related protein 10 2 MPM2/C14orf159 NM_024952.4 14q32.12 t1727g V→G −3 chromosome 14 ORF159 2 TM9SF1 NM_006405.5 14q11.2 c2014t R→M −3 transmembrane 9 superfamily member 1 LOH due to epigenetic silencing 4 PARF/C9orf86 NM_024718.2 9q34.3 c2110g P→R −2 Chromosome 9 ORF 86 4 AVEN NM_020371.2 15q13.1 a784c E→A −1 apoptosis, caspase activationm inhhibiter 4 PSMD8BP1/NOB1 NM_014062.1 16q22.3 a1074g Q→R 1 NIN1/RPN12 binding protein 1 homolog LOH due to X inactivation 2 MPM1/CXorf34 NM_024917.4 Xp22.1 g1780a G→R −2 Chromosome X ORF 34 RNA Editing 4 FLJ00312/CTGLF6 XM_374801.3 10q11.22 t1721a D→E 2 Centraurin, gamma-like family, member 6 

1. A method for surveillance for malignant mesothelioma (MM) in a subject comprising: a. detecting the presence of at least one genetic mutation listed in Tables 1 and 2, and disclosed TNFRSF1A mutations in FIG. 1 in a biological sample obtained from the subject; and b. subjecting the subject to at least one addition diagnostic test selected from the group consisting of chest X-ray, MRI, CT scan, PET scan, thoracentesis, mediastinoscopy, echocardiogram and thoracoscopy when at least one mutation is detected. 2.-53. (canceled)
 54. The method of claim 1, wherein the subject is not been differentially diagnosed with MM.
 55. The method of claim 1, wherein the subject has prior exposure to asbestos, lives or has lived with a person who works with asbestos, or has no known prior exposure to asbestos.
 56. The method of claim 1, wherein the method is performed on a schedule selected from the group consisting of monthly, once every two months, once every three months, once every two months, once every five months, and once every six months and once yearly.
 57. The method of claim 1, wherein the subject is asymptomatic for a common respiratory ailment or has at least one symptom selected from the group anemia, blood clotting disorder, bowel obstruction, chest pain, persistent dry or raspy cough, coughing up blood (hemoptysis), shortness of breath (dyspnea), pain in the lower back or rib area, painful breathing, development of lumps under the skin on the chest, difficulty with swallowing (dysphagia), night sweats or fever, nausea, unexplained weight loss, fatigue, abdomen, pericardium, peritoneal and/or pleural effusion.
 58. The method of claim 1, wherein the detecting further comprising extracting the deoxyribonucleic acid from the biological sample prior to analysis for genetic mutations.
 59. The method of claim 1, further comprising selecting a subject who is at risk of developing MM.
 60. The method of claim 1, wherein when at least one mutation is detected, the method further comprising assigning a subtype of MM to the subject based the profile of gene mutations.
 61. The method claim 60, further comprising inputting the profile of gene mutations into a computer system equipped with a computer software for analyzing the profile of gene mutations and assigning a subtype of MM to the profile of gene mutations.
 62. A method of classifying subtypes of malignant mesothelioma (MM) based on profiles of genetic mutations in a population of subjects having MM comprising: a. providing a genetic mutation profile database comprising profiles of genetic mutation of the genes of Tables 1 and 2 and disclosed TNFRSF1A mutations at the specific location indicated in Tables 1 and 2 and disclosed TNFRSF1A mutations in FIG. 1 from a population of subjects having MM and prior to any treatment; b. applying the genetic mutation database to a clustering algorithm which analyzes and identifies at least two separate and distinct clusters within the database, wherein each cluster comprising a collection of genetic mutations of Tables 1 and 2 and disclosed TNFRSF1A mutations in FIG. 1; c. sorting the population of subjects having MPM into the at least two separate and distinct clusters identified by the clustering algorithm; d. monitoring the treatment regimen and prognosis of the subjects separated into the clusters of step c; e. correlating the treatment regimen and prognosis of the subjects with the subject's designated cluster; f. determining which treatment regimen for each cluster result in at least 2 fold increase in survival over the median survival time; and g. associating the treatment regimen of step f with the respective cluster to form a subtype.
 63. A method of subtyping malignant mesothelioma (MM) in a subject comprising: a. detecting for the presences of all the mutations disclosed in Tables 1 and 2 and disclosed TNFRSF1A mutations in FIG. 1 to generate a profile of gene mutations; b. comparing the profile of gene mutations with a collection of genetic mutations associated with each subtypes identified in the method of claim 62; and c. assigning a subtype of MPM when the profile of gene mutations of the subject matches the collection by a 70 percentile.
 64. A method for treating malignant mesothelioma (MM) in a subject comprising: a. categorizing the MM to a subtype according to the method of claim 63; and b. administering an effective treatment regime to the subject based on the subtype.
 65. A method for treating MM in a subject comprising administering to a subject in need thereof a therapeutically effective amount of an agent that increases the expression of a tumor necrosis factor receptor superfamily member 1A (TNFRSF1A).
 66. The method of claim 65, wherein the agent is thalidomide or lenalidomide (levlimid).
 67. The method of claim 65, wherein the agent is a nucleic acid sequence comprising the human sequence TNFRSF1A mRNA sequence NM_(—)001065.2.
 68. The method of claim 65, wherein the agent is a nucleic acid sequence comprising SEQ. ID. NO:1 or a vector or DNA construct comprising a nucleic acid sequence SEQ. ID. NO:1. 